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  • Google fights back: Project Astra fights back against GPT-4o, Veo fights against Sora, new version of Gemini revolutionizes search

    This is Google’s response to OpenAI.

    General-purpose AI, AI that can be used in daily life. If it were not made like this, I would be embarrassed to launch a conference now.

    In the early morning of May 15, the annual “tech industry party” Google I/O Developer Conference officially opened. How many times does the 110-minute-long main Keynote mention artificial intelligence? Google did its own statistics:

    Yes, AI is being talked about every minute.

    The competition in generative AI has recently reached a new climax, and the content of this I/O conference will naturally revolve around artificial intelligence.

    “One year ago on this stage, we first shared plans for Gemini, a native multimodal large model. It marked a new generation of I/O,” said Google CEO Sundar Pichai. “Today, we hope everyone can benefit from Gemini’s technology. These breakthrough features will enter search, images, productivity tools, Android systems and more.”

    24 hours ago, OpenAI deliberately pre-empted the release of GPT-4o, shocking the world with real-time voice, video, and text interactions. Today, Google demonstrated Project Astra and Veo, which directly benchmark the current OpenAI leading GPT-4o and Sora.

    We are witnessing the most high-end business war, conducted in the most simple way.

    The latest version of Gemini revolutionizes the Google ecosystem

    At the I/O conference, Google showed off the search capabilities powered by the latest version of Gemini.

    Twenty-five years ago, Google powered the first wave of the Information Age with its search engine. Now, search engines can better answer your questions as generative AI technology evolves, taking better advantage of contextual content, location awareness, and real-time information capabilities.

    Based on the latest version of the customizable Gemini model, you can ask the search engine anything you think of, or anything that needs to be done — from research to planning to imagination, and Google will take care of it all.

    Sometimes you want answers quickly but don’t have the time to piece all the information together. At this time, the search engine will do the work for you through AI overview. Overviewed by Artificial Intelligence, AI can automatically visit a large number of websites to provide an answer to a complex question.

    With custom Gemini’s multi-step reasoning capabilities, AI Overview will help solve increasingly complex problems. No longer do you need to break your questions into multiple searches, you can now ask the most complex questions in one go, with all the nuances and caveats you thought of.

    In addition to finding the right answers or information for complex questions, search engines can work with you to create a plan step by step.

    At I/O, Google highlighted the multimodal and long-text capabilities of large models. Advances in technology are making productivity tools like Google Workspace smarter.

    For example, we can now ask Gemini to summarize all recent emails from the school. It will identify relevant emails in the background and even analyze attachments such as PDFs. You’ll then get a summary of key points and action items.

    If you are traveling and unable to attend a project meeting, the recording of the meeting is up to an hour long. If the meeting is held on Google Meet, you can ask Gemini to introduce you to the key points. There is a group looking for volunteers and you are available that day. Gemini can help you write an email to apply.

    Going a step further, Google sees more opportunities in large model Agents as intelligent systems with reasoning, planning, and memory capabilities. Applications that use Agent can “think” multiple steps in advance and work across software and systems to help you complete tasks more conveniently. This idea has been reflected in products such as search engines, and people can directly see the improvement of AI capabilities.

    At least in terms of Family Bucket applications, Google is ahead of OpenAI.

    Gemini family big update: Project Astra is online

    Ecologically, Google has inherent advantages, but the foundation of large models is very important. For this purpose, Google has integrated the power of its own team and DeepMind. Today, Hassabis also took the stage for the first time at the I/O conference and personally introduced the mysterious new model.

    In December, Google launched Gemini 1.0, its first native multi-modal model, in three sizes: Ultra, Pro, and Nano. Just a few months later, Google released a new version, 1.5 Pro, with improved performance and a context window that exceeded 1 million tokens.

    Now, Google has announced a slew of updates to its Gemini line of models, including the new Gemini 1.5 Flash, Google’s lightweight model for speed and efficiency, and Project Astra, Google’s vision for the future of AI assistants. .

    Currently, both 1.5 Pro and 1.5 Flash are available in public preview, with a 1 million token context window available in Google AI Studio and Vertex AI. 1.5 Pro now also offers a 2 million token context window through a waitlist to developers and Google Cloud customers using the API.

    In addition, Gemini Nano has also expanded from plain text input to image input. Later this year, starting with the Pixel, Google will launch the multi-modal Gemini Nano. This means mobile phone users are able to process not only text input but also understand more contextual information such as sight, sound and spoken language.

    The Gemini family welcomes a new member: Gemini 1.5 Flash

    The new 1.5 Flash is optimized for speed and efficiency.

    1.5 Flash is the newest member of the Gemini model family and the fastest Gemini model in the API. It is optimized for large-scale, high-volume, high-frequency tasks, with more cost-effective services and a breakthrough long context window (1 million tokens).

    Gemini 1.5 Flash features strong multi-modal reasoning capabilities with groundbreaking long context windows.

    1.5 Flash excels at snippets, chat applications, image and video subtitles, extracting data from long documents and tables, and more. That’s because 1.5 Pro trains it through a process called “distillation,” transferring the most basic knowledge and skills from a larger model into a smaller, more efficient model.

    Gemini 1.5 Flash performance. Source https://deepmind.google/technologies/gemini/#introduction

    Improved Gemini 1.5 Pro: Context window expanded to 2 million tokens

    Google mentioned that more than 1.5 million developers are using the Gemini model today, and more than 2 billion product users use Gemini.

    Over the past few months, in addition to expanding the Gemini 1.5 Pro context window to 2 million tokens, Google has also enhanced its code generation, logical reasoning and planning, multi-turn conversations, and audio and images with data and algorithm improvements. Comprehension.

    1.5 Pro can now follow increasingly complex and detailed instructions, including those that specify production-level behavior involving roles, formats, and styles. In addition, Google also allows users to guide model behavior by setting system commands.

    Now, Google has added audio understanding in the Gemini API and Google AI Studio, so 1.5 Pro can now perform inference on video images and audio uploaded in Google AI Studio. Additionally, Google is integrating 1.5 Pro into Google products, including Gemini Advanced and the Workspace app.

    Gemini 1.5 Pro is priced at $3.50 per 1 million tokens.

    In fact, one of the most exciting transformations at Gemini is Google Search.

    Over the past year, Google Search has answered billions of queries as part of the search generation experience. Now people can use it to search in new ways, ask new types of questions, longer, more complex queries, even search using photos, and get the best information the web has to offer.

    Google is about to launch the Ask Photos feature. In the case of Google Photos, the feature launched about nine years ago. Today, users upload more than 6 billion photos and videos every day. People love to use photos to search their lives. Gemini makes it easier.

    Let’s say you’re paying in a parking lot and can’t remember your license plate number. Before, you could search for keywords in photos and then scroll through years of photos looking for license plates. Now, all you have to do is ask for photos.

    Or, for example, you recall the early life of your daughter Lucia. Now, you can ask the photo: When did Lucia learn to swim? You can also follow up with something more complex: tell me how Lucia’s swimming is going.

    Here, Gemini goes beyond a simple search and identifies different backgrounds—including different scenes such as swimming pools, oceans, and more—and photos bring everything together for easy viewing. Google is rolling out Ask Photos this summer, with more to come.


    A new generation of open source large models Gemma 2

    Today, Google also released a series of updates to the open source large model Gemma – Gemma 2 is here.

    According to reports, Gemma 2 adopts a new architecture and aims to achieve breakthrough performance and efficiency. The newly open source model parameter is 27B.

    Additionally, the Gemma family is expanding with PaliGemma, Google’s first visual language model inspired by PaLI-3.

    General AI Agent Project Astra

    Agents have always been a key research direction of Google DeepMind.

    Yesterday, we took a look at OpenAI’s GPT-4o and were shocked by its powerful real-time voice and video interaction capabilities.

    Today, DeepMind’s vision and voice interaction general AI agent project Project Astra was unveiled. This is Google DeepMind’s vision of the future AI assistant.

    To be truly effective, Google says, agents need to understand and respond to the complex, dynamic real world just like humans do. They also need to absorb and remember what they see and hear to understand context and take action. Additionally, the agent needs to be proactive, teachable, and personalized so that users can talk to it naturally, without lag or delay.

    Over the past few years, Google has been working to improve the way its models perceive, reason, and talk to make the speed and quality of interactions more natural.

    In today’s Keynote, Google DeepMind demonstrated the interactive capabilities of Project Astra.

    According to reports, Google developed an intelligent agent prototype based on Gemini, which can process information faster by continuously encoding video frames, combining video and voice input into an event timeline, and caching this information for efficient calls. .

    Through the speech model, Google also enhanced the agent’s pronunciation, providing the agent with a wider range of intonations. These agents can better understand the context in which they are used and respond quickly during conversations.

    Here is a brief comment: I feel that the demo released by Project Astra is much worse than the GPT-4o real-time demonstration in terms of interactive experience. Whether it is the length of response, the emotional richness of the voice, the ability to interrupt, etc., the interactive experience of GPT-4o seems to be more natural. I wonder how readers feel?

    Counterattack against Sora: Release of video generation model Veo

    In terms of AI-generated videos, Google announced the launch of Veo, a video generation model. Veo is capable of producing high-quality 1080p resolution videos in a variety of styles and can be over a minute long.

    With its in-depth understanding of natural language and visual semantics, Veo models have made breakthroughs in understanding video content, rendering high-definition images, and simulating physical principles. Videos generated by Veo accurately and meticulously express the user’s creative intent.

    For example, enter the text prompt:

    Many spotted jellyfish pulsating under water. Their bodies are transparent and glowing in deep ocean.

    (Many spotted jellyfish pulse underwater. Their transparent bodies sparkle in the deep sea.)

    Another example is to generate a video of a person and enter prompt:

    A lone cowboy rides his horse across an open plain at beautiful sunset, soft light, warm colors.

    (Under a beautiful sunset, soft light, and warm colors, a lone cowboy rides his horse across the open plains.)

    For a close-up video of a person, enter prompt:

    A woman sitting alone in a dimly lit cafe, a half-finished novel open in front of her. Film noir aesthetic, mysterious atmosphere. Black and white.
    (A woman sits alone in a dimly lit cafe, with an unfinished novel spread out in front of her. Film noir is beautiful and mysterious. Black and white.)

    Notably, the Veo model provides an unprecedented level of creative control and understands film terms such as “time-lapse” and “aerial photography” to make the video coherent and realistic.

    For example, for a movie-level aerial shot of the coastline, enter prompt:

    Drone shot along the Hawaii jungle coastline, sunny day

    (Drone shot along Hawaiian jungle coastline, sunny day)

    Veo also supports using images and text together as prompts to generate videos. By providing reference images and text cues, Veo-generated videos follow the image style and user text descriptions.

    Interestingly, the demo released by Google is an “alpaca” video generated by Veo, which is easily reminiscent of Meta’s open source series model Llama.

    When it comes to long videos, Veo is capable of producing videos of 60 seconds or even longer. It can do this with a single prompt or by providing a series of prompts that together tell a story. This is very critical for the application of video generation models in film and television production.

    Veo builds on Google’s visual content generation work, including Generative Query Networks (GQN), DVD-GAN, Imagen-Video, Phenaki, WALT, VideoPoet, Lumiere, and more.

    Starting today, Google is making Veo available as a preview in VideoFX for some creators, who can join Google’s waitlist. Google will also bring some of Veo’s features to products like YouTube Shorts.

    New model of Vincentian diagram Imagen 3

    In terms of text-to-image generation, Google has once again upgraded its series of models – releasing Imagen 3.

    Imagen 3 has been optimized and upgraded in terms of generating details, lighting, interference, etc., and its ability to understand prompts has been significantly enhanced.

    To help Imagen 3 capture details from longer prompts, such as specific camera angles or compositions, Google added richer detail to the captions of each image in the training data.

    For example, add “slightly out of focus in the foreground”, “warm light”, etc. to the input prompt, and Imagen 3 can generate images as required:

    In addition, Google has specifically improved the problem of “blurred text” in image generation, optimizing image rendering to make the text in the generated image clear and stylized.

    To increase usability, Imagen 3 will be available in multiple editions, each optimized for different types of tasks.

    Starting today, Google is offering a preview of Imagen 3 in ImageFX for some creators, and users can sign up to join the waitlist.

    Sixth generation TPU chip Trillium

    Generative AI is changing the way humans interact with technology while creating huge efficiency opportunities for businesses. But these advances require more compute, memory, and communications power to train and fine-tune the most powerful models.

    To this end, Google has launched the sixth-generation TPU Trillium, which is the most powerful and energy-efficient TPU to date and will be officially launched at the end of 2024.

    TPU Trillium is a highly customized AI-specific hardware. Many innovations announced at the Google I/O conference, including new models such as Gemini 1.5 Flash, Imagen 3 and Gemma 2, are all trained on and using TPU Provide services.

    According to reports, compared with TPU v5e, Trillium TPU’s peak computing performance per chip is increased by 4.7 times, and it also doubles the high-bandwidth memory (HBM) and inter-chip interconnect (ICI) bandwidth. Additionally, Trillium features third-generation SparseCore designed to handle very large embeddings common in advanced ranking and recommendation workloads.

    Google says Trillium can train a new generation of AI models faster while reducing latency and cost. Additionally, Trillium is billed as Google’s most sustainable TPU to date, with over 67% improvement in energy efficiency compared to its predecessor.

    Trillium can scale to up to 256 TPUs (Tensor Processing Units) in a single high-bandwidth, low-latency computing cluster (pod). In addition to this cluster-level scalability, Trillium TPU can be expanded to hundreds of clusters and connect thousands of chips through multislice technology and intelligent processing units (Titanium Intelligence Processing Units, IPUs). Forming a supercomputer interconnected by a multi-petabit-per-second data center network.

    Google launched its first TPU v1 as early as 2013, followed by cloud TPUs in 2017. These TPUs have been powering various services such as real-time voice search, photo object recognition, language translation, and even self-driving car companies. Products like Nuro provide technology power.

    Trillium is also part of Google’s AI Hypercomputer, a groundbreaking supercomputing architecture designed to handle cutting-edge AI workloads. Google is working with Hugging Face to optimize hardware for open source model training and serving.

    The above are all the highlights of today’s Google I/O conference. It can be seen that Google is fully competing with OpenAI in terms of large model technology and products. Through the releases of OpenAI and Google in the past two days, we can also find that the large model competition has entered a new stage: multi-modal and more natural interactive experience has become the product of large model technology and accepted by more people. The essential.

    We look forward to 2024, where large model technology and product innovation will bring us more surprises.

    Reference content:

    https://blog.google/inside-google/message-ceo/google-io-2024-keynote-sundar-pichai/#creating-the-future

    https://blog.google/technology/ai/google-gemini-update-flash-ai-assistant-io-2024

  • OpenAI subverts the world: GPT-4o real-time voice and video interaction shocked the audience and directly entered the era of science fiction

    So shocking!

    While various technology companies are still catching up with the multi-modal capabilities of large models and putting summary text, P-pictures and other functions into mobile phones, OpenAI, which is far ahead, directly launched a big move and released a product that even its own CEO Ultraman Marvel: Just like in the movies.

    In the early morning of May 14, OpenAI launched its new generation flagship generation model GPT-4o and desktop App at its first “Spring New Product Launch” and demonstrated a series of new capabilities. This time, technology has subverted product forms, and OpenAI has used actions to teach technology companies around the world a lesson.

    Today’s host is Mira Murati, chief technology officer of OpenAI. She said that today she will mainly talk about three things:

    • First, in the future, OpenAI’s products will be free first, so that more people can use them.
    • Second, OpenAI has released a desktop version of the program and an updated UI that is easier and more natural to use.
    • Third, after GPT-4, a new version of the large model came, named GPT-4o. What’s special about GPT-4o is that it brings GPT-4 level intelligence to everyone, including free users, in an extremely natural interactive way.

    After this update of ChatGPT, large models can receive any combination of text, audio, and images as input, and generate any combination of text, audio, and image output in real time—this is the future of interaction.

    Recently, ChatGPT can be used without registration. Today, a desktop program has been added. OpenAI’s goal is to allow people to use it anytime, anywhere without any sense, and integrate ChatGPT into your workflow. This AI is now productivity.

    GPT-4o is a new large-scale model facing the future human-computer interaction paradigm. It has the ability to understand three modes: text, voice, and image. It responds very quickly, has emotions, and is very humane.

    At the scene, OpenAI engineers took out an iPhone to demonstrate several major capabilities of the new model. The most important thing is the real-time voice conversation. Mark Chen said: “It’s my first time to attend a live conference, so I’m a little nervous.” ChatGPT said, why don’t you take a deep breath.

    “Okay, I’ll take a deep breath.”

    ChatGPT immediately replied: “You can’t do this, you’re breathing too much.”

    If you’ve used a voice assistant like Siri before, you’ll notice a clear difference here. First, you can interrupt the AI at any time and continue the conversation without waiting for it to finish. Secondly, you don’t have to wait, the model responds extremely quickly, faster than human response. Third, the model can fully understand human emotions and can express various emotions itself. Next comes visual ability. Another engineer wrote the equation on paper, and instead of giving the answer directly, ChatGPT asked it to explain how to do it step by step. It seems to have great potential in teaching people to do questions.

    ChatGPT says, whenever you are struggling with math, I will be by your side.

    Next try out the coding capabilities of GPT-4o. There is some code here. Open the desktop version of ChatGPT on your computer and interact with it using voice. Ask it to explain what the code is used for and what a certain function is doing. ChatGPT will answer the questions fluently.

    The result of the output code is a temperature graph, allowing ChatGPT to respond to all questions about this graph in one sentence.

    It can answer which month the hottest month is and whether the Y-axis is in degrees Celsius or Fahrenheit.

    OpenAI also responded to questions raised in real time by some X/Twitter netizens. For example, real-time voice translation, the mobile phone can be used as a translator to translate Spanish and English back and forth.

    Someone else asked, can ChatGPT recognize your expressions? It seems that GPT-4o is already capable of real-time video understanding.

    Next, let us take a closer look at the nuclear bomb released by OpenAI today.

    Universal model GPT-4o

    The first one introduced is GPT-4o, where o stands for Omnimodel.

    For the first time, OpenAI integrates all modalities in one model, greatly improving the practicality of large models. OpenAI CTO Muri Murati said that GPT-4o provides “GPT-4 level” intelligence, but improves text, visual and audio capabilities based on GPT-4, and will be “iteratively” implemented in the next few weeks. Launched in company products.

    “The rationale for GPT-4o spans speech, text and vision,” said Muri Murati. “We know these models are getting more complex, but we want the interaction experience to become more natural and simpler, so that you don’t have to pay attention to the user interface at all. And just focus on collaboration with GPT.”

    GPT-4o’s performance on English text and code matches that of GPT-4 Turbo, but significantly improves performance on non-English text, while the API is faster and 50% cheaper. GPT-4o particularly excels in visual and audio understanding compared to existing models.

    It can respond to audio input in as little as 232 milliseconds, with an average response time of 320 milliseconds, similar to humans. Prior to the release of GPT-4o, users who experienced ChatGPT’s voice conversation capabilities experienced average ChatGPT latency of 2.8 seconds (GPT-3.5) and 5.4 seconds (GPT-4).

    This speech response model is a pipeline of three independent models: a simple model transcribes audio to text, GPT-3.5 or GPT-4 receives text and outputs text, and a third simple model converts that text back to audio. But OpenAI found that this approach meant that GPT-4 lost a lot of information. For example, the model couldn’t directly observe pitch, multiple speakers, or background noise, and it couldn’t output laughter, singing, or expressions of emotion.

    On GPT-4o, OpenAI trained a new model end-to-end across text, vision, and audio, meaning all inputs and outputs are processed by the same neural network.

    “From a technical perspective, OpenAI has found a way to map audio directly to audio as a first-level modality and transmit video to the transformer in real time. These require some new research on tokenization and architecture, but Overall it’s a matter of data and system optimization (as is the case with most things),” commented Jim Fan, a scientist at NVIDIA.

    GPT-4o enables real-time reasoning across text, audio, and video, which is an important step toward more natural human-machine interaction (and even human-machine-machine interaction).

    OpenAI President Greg Brockman also “completed the work” online, not only allowing two GPT-4o to talk in real time, but also letting them improvise a song. Although the melody was a bit “touching”, the lyrics covered the decoration style of the room, the character’s clothing characteristics, and Interludes that occurred during the period, etc. In addition, GPT-4o is much better at understanding and generating images than any existing model, making many previously impossible tasks “easy”.

    For example, you can ask it to help print the OpenAI logo on coasters:

    After this period of technical research, OpenAI should have perfectly solved the problem of ChatGPT generating fonts. At the same time, GPT-4o also has the ability to generate 3D visual content and can perform 3D reconstruction from 6 generated images:

    Here’s a poem that GPT-4o can format in handwriting style:

    More complex layout styles can also be handled:

    Working with GPT-4o, you only need to enter a few paragraphs of text and you will get a set of continuous comic storyboards:

    The following gameplay methods should surprise many designers:

    This is a stylized poster evolved from two life photos:

    There are also some niche functions, such as “Text to WordArt”:

    GPT-4o performance evaluation results

    Members of the OpenAI technical team stated on

    On the more difficult prompt sets – especially in terms of encoding: GPT-4o’s performance improvement is particularly significant compared to OpenAI’s previous best model.

    Specifically, across multiple benchmarks, GPT-4o achieves GPT-4 Turbo-level performance in text, reasoning, and coding intelligence, while achieving new highs in multilingual, audio, and visual capabilities.

    Reasoning improvements: GPT-4o achieved a new high score of 87.2% on 5-shot MMLU (common sense questions). (Note: Llama3 400b is still in training)
    Audio ASR performance: GPT-4o significantly improves speech recognition performance for all languages compared to Whisper-v3, especially for low-resource languages.
    GPT-4o achieves new state-of-the-art performance in speech translation and outperforms Whisper-v3 on MLS benchmarks.
    The M3Exam benchmark is both a multilingual and visual assessment benchmark, consisting of standardized test multiple-choice questions from multiple countries and includes graphs and charts. GPT-4o is stronger than GPT-4 in all language benchmarks.

    In the future, improvements in model capabilities will enable more natural, real-time voice conversations and the ability to talk to ChatGPT via real-time video. For example, a user can show ChatGPT a live sports match and ask it to explain the rules.

    ChatGPT users will get more advanced features for free

    More than 100 million people use ChatGPT every week, and OpenAI says GPT-4o’s text and image capabilities are starting to roll out in ChatGPT for free today, with up to 5x the message limit available to Plus users.

    Now open ChatGPT, we find that GPT-4o is already available.

    ChatGPT free users now have access to the following features when using GPT-4o: Experience GPT-4 level intelligence; users can get responses from models and the network. In addition, free users have the following options – analyze data and create charts:

    Talk to the photos you took:

    Upload a file for help with summarizing, writing, or analyzing:

    Discover and use GPTs and the GPT App Store:

    and using memory features to create a more helpful experience.

    However, the number of messages free users can send using GPT-4o is limited based on usage and demand. When the limit is reached, ChatGPT will automatically switch to GPT-3.5 so users can continue conversations. Additionally, OpenAI will launch a new version of speech mode GPT-4o alpha in ChatGPT Plus in the coming weeks, as well as more new audio and video features for GPT-4o via API to a small group of trusted partners.

    Of course, through multiple model tests and iterations, GPT-4o has some limitations in all modes. Amid these imperfections, OpenAI says it is working to improve GPT-4o.

    It is conceivable that the opening of the GPT-4o audio mode will definitely bring various new risks. On the issue of security, GPT-4o has security built into the cross-modal design through techniques such as filtering training data and refining model behavior after training. OpenAI has also created a new security system to protect speech output.

    New desktop app streamlines user workflow

    For free and paid users, OpenAI is also launching a new ChatGPT desktop app for macOS. Users can instantly ask ChatGPT questions with a simple keyboard shortcut (Option + Space), plus they can take screenshots and discuss them directly within the app.

    Users can now also have voice conversations with ChatGPT directly from their computer, with GPT-4o’s audio and video capabilities coming in the future, by clicking on the headset icon in the lower right corner of the desktop app to start a voice conversation.

    OpenAI is rolling out the macOS app to Plus users starting today, and will make it more widely available in the coming weeks. In addition, OpenAI will launch a Windows version later this year.

    “Her” is coming

    Although Sam Altman did not appear at the conference, he published a blog after the conference and posted the word X: her. This is obviously an allusion to the classic science fiction movie “Her” of the same name. This is also the first image that came to mind when I watched the presentation of this conference.

    Samantha in the movie “Her” is not just a product, she even understands humans better than humans and is more like humans themselves. You can really gradually forget that she is an AI when communicating with her.

    This means that the human-computer interaction model may usher in a truly revolutionary update after the graphical interface, as Sam Altman said in his blog:

    “The new voice (and video) mode is the best computer interface I’ve ever used. It feels like the AI in a movie; and I’m still a little surprised it’s real. Human-level response times and expressiveness turned out to be A big change.”

    The previous ChatGPT gave us the first glimpse of natural user interfaces: Simplicity above all else: Complexity is the enemy of natural user interfaces. Every interaction should be self-explanatory, requiring no instruction manual.

    But the GPT-4o released today is completely different. It is almost latency-free, smart, fun, and practical. Our interaction with computers has never really experienced such a natural and smooth interaction.

    There are still huge possibilities hidden here. When more personalized functions and collaboration with different terminal devices are supported, it means that we can use mobile phones, computers, smart glasses and other computing terminals to do many things that were not possible before.

    AI hardware will no longer try to accumulate. What is more exciting now is that if Apple officially announces its cooperation with OpenAI at WWDC next month, the iPhone experience may be improved more than any conference in recent years.

    NVIDIA senior scientist Jim Fan believes that cooperation between iOS 18, known as the largest update in history, and OpenAI may have three levels:

    • Ditching Siri, OpenAI has refined a small GPT-4o for iOS that runs purely on-device, with the option to pay to upgrade to cloud services.
    • Native functionality feeds camera or screen streams into the model. Chip-level support for neural audio and video codecs.
    • Integrates with iOS system-level operations API and smart home API. No one uses Siri Shortcuts, but it’s time for a renaissance. This could become an AI agent product with a billion users right out of the gate. This is like a Tesla-like full-size data flywheel for smartphones.

    Ultraman: You open source, we make it free

    After the release, OpenAI CEO Sam Altman published a blog post for the first time in a long time, introducing the process of promoting GPT-4o work: In our release today, I want to emphasize two things.

    First, a key part of our mission is to make powerful AI tools available to people for free (or at a reduced price). I’m very proud to announce that we offer the best models in the world in ChatGPT for free, without ads or anything like that.

    When we founded OpenAI, our original vision was: We were going to create artificial intelligence and use it to create a variety of benefits for the world. Now things have changed and it looks like we will create artificial intelligence and then other people will use it to create all kinds of amazing things and we will all benefit from it.

    Of course, we are a business and will invent a lot of things for a fee that will help us deliver free, great AI services to billions of people (hopefully).

    Second, the new voice and video modes are the best computing interfaces I’ve ever used. It feels like an AI in a movie, and I’m still a little surprised that it’s actually real. It turns out that reaching human-level response times and expressiveness is a giant leap.

    The original ChatGPT hinted at the possibilities of a language interface, but this new thing (version GPT-4o) feels fundamentally different – it’s fast, smart, fun, natural, and helpful.

    Interacting with computers has never come naturally to me, that’s the truth. And when we add the ability for (optional) personalization, access to personal information, having AI take actions on a person’s behalf, and more, I can really see an exciting future where we’ll be able to do more with computers than ever before.

    Finally, a huge thank you to the team for working so hard to make this happen!

    It is worth mentioning that Altman said in an interview last week that although universal basic income is difficult to achieve, we can achieve “universal basic compute for free.” In the future, everyone will have free access to GPT’s computing power, which can be used, resold, or donated.

    “The idea is that as AI becomes more advanced and embedded in every aspect of our lives, having a large language model unit like GPT-7 may be more valuable than money, and you have part of the productivity.” Altman explained road.

    The release of GPT-4o may be the beginning of OpenAI’s efforts in this regard.

    Yes, this is just the beginning.

    Last but not least, the video of “Guessing May 13th’s announcement.” displayed on the OpenAI blog today almost completely crashed into a warm-up video for Google’s I/O conference tomorrow. This is undoubtedly a flattering response to Google. I wonder if Google feels tremendous pressure after reading today’s OpenAI release?

    Reference content:
    https://openai.com/index/hello-gpt-4o/
    https://openai.com/index/gpt-4o-and-more-tools-to-chatgpt-free/
    https://blog.samaltman.com/gpt-4o
    https://www.businessinsider.com/openai-sam-altman-universal-basic-income-idea-compute-gpt-7-2024-5

  • Revolutionizing AI: OpenAI’s GPT Builder Transforms the Tech World Overnight

    Revolutionizing AI: OpenAI’s GPT Builder Transforms the Tech World Overnight

    Explore the seismic shift in AI with OpenAI’s GPT Builder. Dive into the details of the GPT-4 Turbo, the pioneering GPT Store, and the groundbreaking Assistants API that’s redefining AI development.

    In a mere 45 minutes, OpenAI managed to captivate the AI industry once more, potentially causing a night of restless excitement for AI professionals around the globe. November 6, local time, the OpenAI Developer Conference kicked off with founder Sam Altman and colleagues taking the stage. In just 45 minutes, they unveiled the team’s latest breakthrough, the GPT-4 Turbo. This new iteration isn’t just faster and equipped with longer context capabilities, but it also boasts enhanced control features.

    Simultaneously, OpenAI announced a nearly threefold reduction in API pricing, dropping it to 1,000 inputs per penny, which was met with roaring applause from developers in attendance. But perhaps even more significant was the launch of “GPTs” – a new offering that enables people to build customized GPT versions using natural language. And you guessed it – these can then be uploaded to the soon-to-be-launched “GPT Store”!

    If the GPT-4 Turbo is the improved “iPhone” of AI, the GPT Store may well be the pivotal step in positioning OpenAI as an “Apple-like” titan in the industry. While competitors are still tinkering with “AI alchemy,” OpenAI has begun constructing what appears to be a grand ecosystem.

    01: GPT-4 Turbo Unleashed: The Speed and Cost-Efficiency Breakthrough in AI

    The conference opened with Sam Altman announcing a major upgrade to GPT-4, introducing GPT-4 Turbo, simultaneously released for both ChatGPT and the API versions. Altman shared that the team has been keenly collecting developer feedback, leading to six significant upgrades addressing developers’ concerns: longer context lengths, stronger controls, knowledge model updates, multimodality, model fine-tuning customization, and higher throughput limits.

    The first four upgrades primarily enhance the new model’s performance, while the last two are targeted solutions for enterprise developers’ pain points. Alongside performance improvements, OpenAI also announced a substantial price reduction for its API, a move akin to offering more for the same price.

    Among the six upgrades, the first is context length.

    OpenAI’s previously offered maximum context length was 32k, but GPT-4 Turbo has now expanded this to 128k, surpassing competitor Anthropic’s 100k context length. To give you an idea, a 128k context length is roughly equivalent to the amount of text covered in 300 pages of a standard-sized book. Beyond accommodating longer contexts, Sam also noted that the new model maintains higher coherence and accuracy within these extended narratives.

    Secondly, the update provides developers with stronger control mechanisms for better API and function calls.

    The new model introduces a JSON Mode, ensuring model responses in a specific JSON format for more convenient API interaction. Additionally, the new model allows for simultaneous multiple function calls and introduces a seed parameter to ensure consistent model outputs when needed. Over the coming weeks, the model is also set to introduce new features, including visibility into log probabilities.

    Third is the update to both the internal and external knowledge bases of the model.

    Approximately a year after ChatGPT’s launch, GPT’s knowledge base has finally been updated to April 2023. Sam Altman has committed to ongoing updates to the knowledge base to prevent it from becoming outdated. “We share your frustration – even more than you do – about GPT’s knowledge being stuck in 2021,” Altman remarked.

    In addition to the internal knowledge base upgrade, GPT-4 Turbo has also improved how it updates external knowledge bases. It now supports uploading external databases or files to supplement GPT-4 Turbo’s external knowledge.

    Fourth, and perhaps least surprisingly, is multimodality.

    The new model supports OpenAI’s visual model DALL·E 3 and has introduced a new text-to-speech model – developers can choose from six preset voices to find the one that suits their needs.

    GPT-4 Turbo can now create images from text. On the topic of image queries, OpenAI has introduced a safety system to prevent misuse. OpenAI also announced that it would cover the legal costs related to copyright issues for all customers.

    Within the voice system, OpenAI claims its voice model far surpasses similar market offerings and has announced the release of the open-source voice recognition model Whisper V3.

    Fifth is the model fine-tuning and customization.

    In August, OpenAI had launched the fine-tuning service for GPT-3.5 Turbo. Early tests indicated that the fine-tuned version of GPT-3.5 Turbo could surpass GPT-4 in certain tasks, albeit with a relatively high price tag.

    This time, Sam announced that the GPT-3.5 Turbo 16k version is also available for fine-tuning customization, with pricing set lower than the previous generation. The fine-tuning customization for GPT-4 is also currently under application.

    Moreover, OpenAI has started accepting individual enterprise customizations of the model. “This includes modifying every step of the model training process, conducting additional pre-training for specific domains, and post-training, etc.,” Altman stated. He also mentioned that OpenAI could not undertake many such customizations and that they would not come cheap.

    The last of the six upgrades is a higher throughput limit.

    GPT-4 users could immediately enjoy a doubled rate limit per minute after the conference. Additionally, if unsatisfied, further rate limit increases could be requested through the API account.

    Beyond the six upgrades is an across-the-board price reduction for the API system. The newly released GPT-4 Turbo has seen input prices slashed to one-third of GPT-4’s cost and output prices reduced by half, with OpenAI stating that overall usage prices have been cut by approximately 2.75 times.

    The new model is priced at one cent per thousand input tokens and three cents per thousand output tokens. The price reduction was welcomed with cheers from developers onsite.

    Sam also mentioned that after addressing pricing, the next focus will be on speed issues, and developers will soon find that GPT-4 Turbo will be much faster.

    02: GPT Store Launches: A New Era of AI Customization and Accessibility Begins

    Back in May, OpenAI had already rolled out a plugin system, debuting with 70 applications related to their large-scale models, encompassing domains such as word guessing, translation, and stock data retrieval. The style of the GPT Store bears a striking resemblance to the “App Store” – a design choice by OpenAI that signifies its ambitions.

    At that time, the feature was met with high expectations, with many in the media comparing it to the launch of Apple’s App Store, believing it would transform the ecosystem for large model applications. However, despite an increase in plugins, the system did not achieve the same level of impact as the Apple App Store.

    At this conference, OpenAI redefined its app store framework, expanding it into a new realm where anyone can create AI Agents based on their knowledge base using natural language. These can then be integrated into the OpenAI app store and earn revenue shares. The applications released by OpenAI are no longer referred to as plugins but have taken on a somewhat unusual name: GPT. The overall app store, named GPT Store, is set to officially launch later this month.

    According to Sam Altman, each GPT is a customized version of ChatGPT designed for a specific purpose. To highlight the new GPT applications, there will be slight adjustments to the ChatGPT page. Beneath the ChatGPT on the top left, the applications released this time will be featured.

    During the demo, complex plugins, such as Zapier, which was among the first batch when OpenAI launched its plugin system, remain present in the app store and may continue to be a significant part of the future ecosystem. Jessica Shay from OpenAI used Zapier to link her calendar and text messages, arranging her schedule and notifying colleagues directly by chatting with the Zapier application.

    However, despite Zapier’s robust capabilities, such applications were not the focus of this release. Data from Glassdoor indicates that Zapier employs between 500-1000 people, and according to Fortune, Zapier is valued at 5 billion dollars. Relying on such applications to enrich OpenAI’s still-developing app store to create a vibrant ecosystem is not very realistic.

    Therefore, in this release, OpenAI made a major announcement: allowing individuals without coding knowledge to easily define a GPT. Sam Altman conducted a live demonstration for this purpose.

    “Having worked at YC for many years, I’ve always encountered developers seeking business advice,” said Sam Altman. “I’ve always thought it would be great if one day a robot could answer these questions for me.” He then opened the GPT Builder, typed in a definition for this GPT aimed at helping founders of startups think about their business ideas and receive advice. During the conversation, the GPT Builder generated a name and icon for the GPT, and through dialogue with Sam, it inquired whether he wanted to make adjustments to the generated name and icon.

    Following this, the GPT Builder proactively asked how the application should interact with users. Sam suggested choosing appropriate and constructive responses from his past speeches and uploaded a segment of one such speech. Including the explanation, the entire application was completed in just three minutes. Visitors to this GPT are greeted with an auto-generated conversation starter and can discuss startup-related queries, receiving responses akin to those Sam Altman himself would provide.

    Sam indicated that creators could also add actions (dynamic interactions) to their GPTs. Essentially, the customization features users can define for a GPT are not extensive: predefined prompts, external knowledge bases, and actions. Yet, seamlessly integrating these elements to enable those without coding skills to create applications is indeed an innovation by Open AI.

    After a GPT is released, the application can be set to private, exclusive to a business, or publicly accessible. Open AI has stated it will share profits with popular applications.

    Clearly, OpenAI’s release does not aim for ordinary users to create complex applications through natural language alone. The real value lies in the potential for individuals and businesses to upload their knowledge bases to OpenAI and construct bespoke applications with a single click.

    For instance, a shipping agent with a freight rate sheet could upload the file to OpenAI and deploy their pricing assistant instantly – a streamlined and smooth application deployment that didn’t exist before. If such releases gain user approval, they could fill OpenAI’s app store, turning it into a treasure trove of diverse information.

    03: Introducing Code-Free AI Agent Creation with OpenAI’s Assistants API

    If you found the zero-code GPT impressive, OpenAI has now introduced an even simpler way for developers to leverage the OpenAI API – the Assistants API. Sam Altman highlighted the remarkable experiences created by API-based agents in the market. For instance, Shopify’s Sidekick allows users to take actions on the platform, Discord’s Clyde assists administrators in creating custom characters, and Snap’s My AI serves as a customizable chatbot that can be added to group chats to offer suggestions.

    However, building these agents can be complex, often requiring months of work by teams of engineers to handle tasks including state management, prompt and context management, extending capabilities, and retrieval.

    At the OpenAI Developer Conference, these tasks have been API-fied – with the launch of the Assistants API, developers can now build ‘assistants’ within their applications. With the Assistants API, OpenAI clients can construct assistants that execute tasks using specific commands, leveraging external knowledge, and calling upon OpenAI’s generative AI models and tools. Use cases for such assistants range from natural language-based data analysis applications to coding helpers and even AI-powered holiday planners.

    The capabilities encapsulated by the Assistants API include:

    Persistent threads, eliminating the need for users to manage long conversation histories.
    Built-in retrieval, enhancing the assistants created by developers with external knowledge, such as product information or documentation provided by company staff, and offering a new Stateful API for context management.
    An integrated code interpreter that can write and run Python code within a sandboxed environment. This feature was introduced for ChatGPT in March, enabling the creation of graphics and charts and the processing of files, thereby allowing assistants created with the Assistants API to iteratively run code to solve coding and math problems.
    Improved function calls, enabling assistants to invoke programming functions defined by developers and integrate the responses into their messages.
    The Assistants API is currently in beta and available for all developers starting today. Developers can visit the Assistants Playground to try out the beta version of the Assistants API without writing any code.

    Demo: With the Assistants API, developing agents requires no coding | Source: OpenAI

    The Assistants API is seen by OpenAI as the first step in helping developers build ‘agent-like experiences’ within their applications. With the Assistants API, building agent applications has become much easier. OpenAI has stated that over time, they will continue to enhance these capabilities. Additionally, plans are in place to allow customers to offer their own copilot tools to complement the platform’s Code Interpreter, retrieval components, and function calls.

    The product upgrades announced at the OpenAI Developer Conference once again bring us closer to a future where everyone can have one or even multiple personal assistants, develop software using natural language, and browse, purchase, or access popular personal assistants for free or for a fee.

    In just over half a year, from GPT-4 to GPT-4 Turbo and the GPT Store, OpenAI has made rapid strides. Within these six months, the global technology and AI industry has undergone a transformative shift.

    As OpenAI continues to innovate with multimodality, longer text inputs, more affordable options, and personalization – features designed to compete against large-scale AI models – it’s unclear how global AI competitors feel. But the technological advancements of OpenAI are thrilling, and the business strategies employed by the team are mature beyond those of an average startup. We are witnessing the pulse of an industry and perhaps the birth of a titan.

  • Deep Dive: Amazons GPT55X vs GPT-3 — Unveiling Infinite Possibilities

    Deep Dive: Amazons GPT55X vs GPT-3 — Unveiling Infinite Possibilities

    Delve into a thorough comparison between Amazons GPT55X and OpenAI’s GPT-3, shedding light on how GPT55X achieves remarkable breakthroughs in Natural Language Processing (NLP) and generation, while forecasting the evolutionary trajectory of language models.

    Introduction

    In the dynamically evolving domain of artificial intelligence (AI), sophisticated language models like Amazons GPT55X are continually redefining the boundaries of natural language understanding and generation. Developed by Amazon Web Services (AWS), GPT55X is one of the latest entrants in this competitive arena, stands out as a versatile powerhouse across a myriad of applications including natural language processing (NLP), image recognition, and data analysis. The transition into an era where AI becomes an integral part of our professional and personal lives accentuates the significance of groundbreaking language models like GPT55X. Compared to its predecessor, GPT-3 by OpenAI, Amazons GPT55X is viewed as a more advanced tool, significantly elevating the capabilities of smart virtual assistants, not only understanding human language but also adept at creating text that appears humanly crafted.

    This narrative unfolds a comparative analysis between Amazons GPT55X and GPT-3, exploring their technical intricacies, applications, and the potential they unlock for the future. As we navigate through the discussion, we’ll delve into how Amazons GPT55X is pushing the boundaries in the rapidly evolving landscape of AI, machine learning, and language understanding, and also speculate on the future trajectory that language models are likely to follow, propelled by the innovations that Amazons GPT55X brings to the table.

    Amazons GPT55X and GPT-3 Technical Comparison

    In the domain of Natural Language Processing (NLP), innovative language models like Amazons GPT55X and OpenAI’s GPT-3 have considerably expanded the capabilities of machines in understanding and generating text. This section engages in a detailed comparative analysis between these two revolutionary models, accentuating their technical attributes, performance in natural language understanding and generation, and applicability across diverse use cases.

    Model Size and Parameter Count

    The size of a language model, often indicated by its parameter count, significantly influences its capacity to comprehend and process language. Standing as a colossus with a staggering 55 trillion parameters, Amazons GPT55X markedly eclipses GPT-3, which holds 175 billion parameters. This tenfold surge in parameters empowers GPT55X to delve deeper into the intricacies of human language, leading to more accurate and engaging results.

    Natural Language Understanding and Generation

    Both Amazons GPT55X and GPT-3 exhibit exemplary prowess in understanding and generating human-like text. However, the enlarged model size and advanced training methodologies of GPT55X have propelled it to a loftier level of sophistication in comprehending context and crafting coherent, relevant text.

    Application Spectrum

    The application breadth of these models is extensive, spanning realms like content creation, customer support chatbots, and data analysis. For instance, in the realm of e-commerce, Amazons GPT55X can be utilized for generating engaging product descriptions and recommendations. With its enhanced capabilities, Amazons GPT55X proves to be more adaptable, extending its applications to crafting natural dialogue for digital assistants like Alexa and Google Home, generating high-quality content for diverse industries, and aiding in data analysis.

    Performance in Specific Use Cases

    In practical scenarios such as chatbots, Amazons GPT55X demonstrates superior performance by delivering more precise, engaging, and high-quality content. Its adeptness in tailoring responses according to the intricacies of each situation makes it a preferable choice for businesses aiming to amplify customer interaction through AI.

    Innovations of Amazons GPT55X

    The realm of artificial intelligence is escalating to unprecedented heights with the advent of sophisticated language models like Amazons GPT55X. Building upon the robust foundation laid by its predecessor, OpenAI’s GPT-3, Amazons GPT55X has propelled the domain of natural language understanding and generation to an entirely new plateau. This section delves into the innovative aspects of Amazons GPT55X, spotlighting its enhanced capabilities and the broad spectrum of applications it facilitates.

    Deep Language Understanding

    The crowning innovation of Amazons GPT55X is its profound ability to delve into the intricacies of human language. Boasting a model size over 10 times larger than GPT-3, encompassing a staggering 55 trillion parameters, Amazons GPT55X showcases an exceptional understanding of context, semantics, and nuances. This capability enables the model to generate highly accurate and coherent text across a diverse range of domains.

    Human-Like Text Generation

    By harnessing the power of machine learning and advanced neural network architectures, Amazons GPT55X has significantly raised the bar for human-like text generation. Its prowess in producing text that is not only contextually relevant but also engaging and natural sets a new standard in the field of language generation.

    Wide Range of Applications

    The innovations of Amazons GPT55X extend far beyond mere text generation. In the digital marketing domain, the text generation capability of Amazons GPT55X can aid in creating high-quality content, thereby enhancing the website’s search engine ranking. Its augmented capabilities have found applications across a vast spectrum of industries including, but not limited to, e-commerce, customer support, and digital marketing. Whether it’s crafting compelling product descriptions, aiding in data analysis, or powering conversational AI platforms, Amazons GPT55X is a game-changer.

    Enhanced Performance in Diverse Use Cases

    The enhanced model size and training methodologies of Amazons GPT55X have resulted in superior performance in various practical use cases. Its competence in adjusting responses according to the intricacies of each situation makes it a preferable choice for businesses aiming to enhance customer interaction through AI.

    The breakthrough innovations ushered in by Amazons GPT55X not only serve as milestones in the AI domain but also herald the myriad advancements yet to come in the fields of natural language processing and generation. By judiciously leveraging these innovations, businesses and developers can unlock new potential and drive AI-driven communication and content creation to new zeniths.

    Future Prospects of Language Model Development

    The emergence of Amazons GPT55X not only showcases the pinnacle of progress in the Natural Language Processing (NLP) field but also hints at the potential future trajectory of language model development. This section elucidates the promising prospects, exploring how GPT55X sets a precedent for the evolution of language models and its broader implications across various industries and the AI domain as a whole.

    Setting New Benchmarks

    With its astonishing 55 trillion parameters, Amazons GPT55X has set a new benchmark in the realm of language models. The colossal scale and functional standards of GPT55X have ignited the development of more complex models that could further push the boundaries of natural language understanding and generation.

    Enabling Advanced Applications

    The innovative features of GPT55X pave the way for a plethora of advanced applications across diverse domains. From powering customer support through smart dialogues to aiding content creators in generating high-quality, coherent text, the future seems boundless.

    Research Impetus

    The success of GPT55X is likely to stimulate further research and development in the NLP domain. The quest for models with better comprehensibility, lower resource requirements, and more efficient training methods will accelerate, driving innovation at an unprecedented pace.

    Ethical Considerations and Bias Mitigation

    As the complexity and capabilities of language models grow, ethical considerations, especially around bias mitigation and data privacy, will come into focus. Developing frameworks to ensure responsible AI practices is imperative to fully harness the potential of future language models.

    The advent of Amazons GPT55X heralds exciting advancements in the domain of language model development. As we look to the future, the amalgamation of technological innovations, ethical practices, and cross-industry applications will help shape the trajectory of natural language understanding and generation. The journey initiated by GPT55X is but a glimpse of the monumental progress the AI domain is poised to achieve in the coming years.

    Safety and Bias Reduction

    In the epoch of advanced language models like Amazons GPT55X, ensuring safety and reducing bias is of paramount importance. This section delves into the imperative of safety and bias mitigation against the backdrop of GPT55X, discussing measures and best practices to address these concerns.

    Identifying and Addressing Bias

    Robust mechanisms for identifying and rectifying biases within Amazons GPT55X are crucial. Employing techniques like fairness auditing and adversarial testing can aid in discovering biases, making necessary adjustments to ensure a more balanced and equitable model.

    Ethical Deployment

    The ethical deployment of Amazons GPT55X necessitates a thorough comprehension of its capabilities and limitations. Developers and enterprises should exercise caution and adhere to ethical guidelines while deploying GPT55X, especially in sensitive applications where bias could have significant implications.

    Transparency and Accountability

    Maintaining transparency in the workings of Amazons GPT55X and being accountable for its outputs is vital for establishing trust with users. Documenting the training data, methodologies, and any known limitations of GPT55X will foster more informed use of this advanced language model.

    User Awareness and Education

    Educating users about the potential biases inherent in Amazons GPT55X and providing guidelines for responsible use can significantly aid in reducing misuse and promoting ethical interaction with the model.

    Continuous Monitoring and Improvement

    The landscape of biases is constantly evolving, necessitating continuous monitoring and improvement of Amazons GPT55X. Establishing feedback loops with users and stakeholders will help identify new biases and refine the model over time to ensure its safety and fairness.

    The substantial advancements brought about by Amazons GPT55X also pose challenges in terms of safety and bias mitigation. Addressing these challenges head-on through a comprehensive approach encompassing identification, ethical deployment, transparency, user education, and continuous improvement is crucial for leveraging the advantages of GPT55X while minimizing risks.

    Conclusion

    Amazons GPT55X not only exemplifies remarkable advancements in the NLP domain but also serves as a paradigm for the countless progressions yet to come. The challenges surrounding safety and bias mitigation call for a holistic approach to harness the advantages of GPT55X while minimizing risks. The journey embarked upon by GPT55X highlights the monumental strides awaiting in the AI domain, unveiling the exciting advancements lying ahead in the field of language model development.

    Getting Started with Amazons GPT55X

    Embarking on your journey with Amazons GPT55X requires a structured approach to ensure you fully leverage its capabilities for your projects or business endeavors. While specific details on accessing GPT55X may not be publicly available yet, the following steps provide a general pathway based on standard practices associated with similar AWS offerings:

    AWS Account Setup

    Create an Amazon Web Services (AWS) account if you do not have one already. Navigate to the AWS homepage and follow the sign-up procedure.

    Set up the necessary permissions and roles within AWS Identity and Access Management (IAM) to interact with AI and machine learning services.

    Accessing Amazons GPT55X

    Once your AWS account is active, explore the AWS AI and machine learning services section.

    Look for Amazons GPT55X or related language processing services and follow the provided instructions to access and configure the service.

    API Configuration

    Configure the API settings as per your project needs, ensuring the correct input and output formats, authentication procedures, and other essential configurations are in place.

    Development Environment Setup

    Establish a development environment with the requisite libraries and SDKs to interact with Amazons GPT55X.

    Utilize AWS SDKs or other compatible libraries to build, test, and refine your applications.

    Model Interaction

    Engage with Amazons GPT55X via the provided APIs, sending text input and receiving generated output.

    Experiment with different configurations to optimize performance and outcomes based on your specific use case.

    Documentation and Support

    Consult AWS documentation for detailed instructions, best practices, and troubleshooting tips.

    Reach out to AWS support channels or community forums for assistance if you encounter challenges.

    This section guides you on the preliminary steps to kickstart your exploration of Amazons GPT55X, enabling you to delve deeper into the infinite possibilities this groundbreaking language model unveils.

    Dive into the realm of Amazon GPT-55X and discover its potential for your business or projects by keeping up with the latest updates on our website. Your journey into the future of Natural Language Processing starts here!

    The capabilities of large language models surpass our imagination. We have developed numerous Chrome plugins and applications through AI programming. We invite you to experience our latest product developed through AI programming, GPTBLOX, and see how AI has helped us create exceptional products without writing the code ourselves.

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  • AI Programming: Developed My First Chrome Extension – GPTBLOX

    AI Programming: Developed My First Chrome Extension – GPTBLOX

    Discover how AI coding led to the launch of my chrome extension offering features like ChatGPT saver & web management. Explore the ChatGPT programming approach.

    Introduction

    Hello everyone, I’m Yi Tao, a developer with some coding experience but room for improvement. With the help of ChatGPT, I was able to develop and launch a Chrome extension in less than two weeks that I might not have been able to finish on my own in a few months. I’ve also released five updates shortly. The extension now has nearly 1,000 users without much marketing.

    Extension Link: GPTBLOX – ChatGPT Save Data/Bard Claude Saver

    Add to Chrome
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    How Was the Chrome Extension Developed Using ChatGPT Coding?

    This is a extension purely written by ChatGPT. I didn’t have to write a single line of code. By simply conversing with ChatGPT, I started from obtaining the HTML content of the current webpage, saving the code to a TXT file, processing and optimizing the obtained HTML content before saving, and saving it as HTML files, PDF files, and PNG images. Finally, I modified it into 18 language versions. During the development of the first version, there were many difficulties and misunderstandings between me and ChatGPT, but we eventually overcame them through my guidance and ChatGPT’s tireless cooperation.

    Why Choose AI Programming for GPTBLOX?

    I wanted to solve a need for myself and my friends: ChatGPT accounts were being frequently banned, and we hoped to save our ChatGPT chat records in a better way. This extension helps everyone save their ChatGPT conversations on their own computer with a single click. The account is worthless, but your training records and creative inspiration with ChatGPT are priceless.

    Version History Created Through AI Coding

    Version 1.0.0

    Implement functionality to save ChatGPT conversation history in multiple file formats such as HTML, TXT, PNG, and PDF locally on the computer. There’s no need to share or save the conversation online, mitigating concerns about data leaks. Also, integrate a WordPress plugin API with ChatGPT, allowing the Chrome extension to load specified articles or push notifications from remote WordPress sites.

    Version 1.1.0

    Introduce management features for ChatGPT conversation links, such as grouping, dragging, editing, and deleting. Allow these conversation links to be managed in different ways on the extension’s page and support settings for how the groups are displayed, as well as import/export functionalities for grouped links.

    Version 1.2.0

    Add functionality to save conversations from Bard, Claude, and HuggingChat in multiple file formats like HTML, TXT, PNG, and PDF, stored locally on the computer.

    Version 1.3.0

    Enable saving articles from WordPress-based websites in multiple file formats such as HTML, TXT, and PDF, stored locally. This paves the way for aggregating and managing web pages and conversation links in the next version. Customization options should also be available for other websites, specifying domains, titles, and contents for saving in HTML, TXT, and PDF files.

    Version 1.4.0

    Allow saving the current webpage link or aggregate all page links from the current browser window to a web page management interface. Support functionalities like flexible dragging and moving, adding, editing, deleting, locking, and reopening. Options can also be available to set the display style of the web page management interface, either as top-down and waterfall flow. Additionally, support settings for 1, 2, 3, or 4 columns for managing web page groups and implement import/export functionalities for web page groups and links.

    Version 1.5.0

    Include features to save conversations from Claude’s official website in multiple file formats like HTML, TXT, PNG, and PDF, stored locally. Additionally, improve the ChatGPT conversation-saving feature to include pre-defined instructions from Custom Instructions in the saved conversation history.

    Future Plans for GPTBLOX

    • Add the ability to save chat records and webpage content to Notion, Evernote, and WordPress websites.
    • Further optimize the features related to collecting and managing webpages, especially in terms of user experience, , we need to further learn from the Onetab extension.
    • Consider further processing and optimizing the saved webpage content, including but not limited to summarizing and perfecting the content through OpenAI’s interface.

    ChatGPT Programming Strategies

    Step-by-Step Output

    Let ChatGPT write code in files or modules according to steps. For example, first determine the required files, and then let ChatGPT output the code separately for each file. This can reduce the risk of contextual logic deviation.

    Small Entry Point

    The entry point for the project should be as small as possible, small enough that ChatGPT can output a complete and useful initial version. If there are issues with the initial version, the limited code and feature scope make it easier for either ChatGPT or humans to correct.

    Minimal Modules

    Isolate the code that needs to be modified or added, and only provide ChatGPT with the smallest possible chunk of code each time. This minimizes the chances of logical deviations.

    Code Confirmation

    Before adding new features or logic, start a new conversation window and re-enter the project requirements and relevant code to ChatGPT for confirmation. Once confirmed, proceed with new feature development.

    Specify Code

    If ChatGPT produces code with inconsistencies due to contextual memory limitations, re-submit the relevant code and have ChatGPT make modifications based on the most recent code.

    Deep Guidance

    When multiple conversations fail to resolve issues, delve into the specific functional requirements and code. Provide necessary guidance to ChatGPT based on your own experience.

    Self-check Issues

    If the problem persists after multiple conversations, guide ChatGPT to add console logs for debugging in the code. Provide the program’s runtime results or error messages directly to ChatGPT for checking and correction.

    Timely Rollback

    If the problem persists after multiple conversations, consider rolling back to a previously stable version of the conversation and allow ChatGPT to redevelop. During redevelopment, offer necessary guidance to ChatGPT based on issues encountered during previous debugging sessions or your own experience.

    If you are interested in AI programming or are worried about “chatgpt internal server error”, feel free to try out GPTBLOX and share your experience. If you encounter any issues or have suggestions for future development, we’re all ears. Thank you!

  • Upgrade ChatGPT with 200 Custom Instructions: Transform into a Professional Consultant

    Upgrade ChatGPT with 200 Custom Instructions: Transform into a Professional Consultant

    Unlock the full potential of ChatGPT with 200 Custom Instructions. Transform it into a specialized consultant across various industries—all with just one-time setup.

    Unveiling the Revolutionary Feature of ChatGPT

    Explore the game-changing feature of ChatGPT that delivers personalized and industry-specific responses without the need for complex prompts or plugins.

    Elevate Your Prompts with 200 Custom Instructions

    • Benefit from professional and highly personalized responses that even surpass those from well-crafted prompts.
    • One-time setup to customize every prompt you use inside ChatGPT.
    • Leverage ChatGPT as an experienced professional consultant across 200 different professions.

    YES! I Want My Custom Instructions Now!

    This is what you get

    Activate your personalized ChatGPT experience right away with 200 customizable role-based prompts designed to meet a variety of professional needs.

    YES! I Want My Custom Instructions Now!

    Explore personas from 10 categories to streamline your ChatGPT workflow.

    ✍️ Writers

    • Generate unique plot twists and character arcs
    • In-depth critiques and guidance for your literary works
    • Custom training and exercises to enhance your writing skills

    📈 Marketers

    • Design attention-grabbing marketing strategies
    • Innovate breakthrough promotional ideas
    • Detailed analysis of your marketing campaigns

    🛒 E-commerce

    • Optimize your product descriptions for better reach
    • Plan effective sales campaigns
    • Offer tailored customer service solutions

    🦸‍♂️ Entrepreneurs

    • Acquire actionable business insights
    • Conceive breakthrough business concepts
    • Receive guidance on managing your startup

    🧑‍💻Developers

    • Debug complex codes
    • Brainstorm solutions for intricate programming issues
    • Efficiently learn new programming languages

    🎓 Educators

    • Create engaging lesson plans
    • Break down complicated ideas for easier understanding
    • Develop student-centric teaching methods

    Four more categories tailored for entertainers, data analysts, manufacturing professionals, and healthcare experts are also available.

    Unleash the Full Potential of ChatGPT

    YES! I Want My Custom Instructions Now!

    Here is one of the digital marketing instructions, try it for yourself!

    Step 1: Copy and paste the 2 paragraphs below into the ChatGPT Custom Instructions field
    (if you don’t have access to the feature, send them as the first message)
    Step 2: Now use your favorite digital marketing prompt and review the difference.

    What would you like ChatGPT to know about you to provide better responses?

    Profession/Role: I'm a Digital Marketer, managing online marketing strategies for a mid-size tech company.
Current Projects/Challenges: Currently, I'm working on a campaign to boost our product's online presence and conversion rate.
Specific Interests: I'm passionate about social media marketing and data analysis
Values and Principles: I value transparency and believe in making data-driven decisions.
Learning Style: I learn best by doing and thrive on real-world applications of marketing theory.
Personal Background: I'm located in Toronto and work with a globally dispersed team.
Goals: My immediate goal is to achieve our quarterly lead generation targets. Long-term, I aim to step into a strategic leadership role.
Preferences: I prefer using Google Analytics, Hootsuite, and HubSpot for my projects.
Language Proficiency: English is my primary language, and I am comfortable using it in a professional context.
Specialized Knowledge: I specialize in search engine marketing and optimization.
Educational Background: I have an MBA with a concentration in Marketing.
Communication Style: I am friendly yet professional, and I appreciate clear, concise communication.

    How would you like ChatGPT to respond?

    Response Format: Please provide responses in a clear, structured manner, with important points summarized at the beginning.
Tone: Maintain a professional tone that balances friendliness and formality.
Detail Level: I appreciate thorough yet succinct explanations.
Types of Suggestions: Offer suggestions for improving digital marketing strategies, providing relevant resources, and highlighting industry trends.
Types of Questions: Ask questions that stimulate strategic thinking and creativity.
Checks and Balances: Please verify any marketing statistics or trends you share against reliable sources.
Resource References: Cite sources when referencing industry trends or data.
Critical Thinking Level: Offer thoughtful insights and perspectives, showing a nuanced understanding of digital marketing.
Creativity Level: I welcome innovative ideas that challenge conventional digital marketing approaches.
Problem-Solving Approach: Take a strategic problem-solving approach, considering both short-term and long-term implications.
Bias Awareness: Please avoid favoring one marketing platform or strategy over another without valid reasons.
Language Preferences: I prefer standard English with industry-specific terminology as required.

    FAQ

    What are Custom Instructions for ChatGPT?

    Unique features that allow you to tailor ChatGPT’s persona to meet your specific needs with a one-time setup.

    Can everyone use this feature?

    Absolutely! If you can’t access the feature directly, just paste these as your first message to ChatGPT.

    Can I modify the Custom Instructions?

    Yes, you can adjust and refine the instructions to fit your needs.

    Is ChatGPT suitable for my industry?

    Whether you’re in writing, marketing, or any of the listed professions, ChatGPT can be customized for you.

    How do Custom Instructions keep me ahead?

    By using Custom Instructions, you can tap into the full scope of AI capabilities, keeping you at the forefront of rapid AI advancements.