In 2016, an artificial intelligence program called AlphaGo from Google’s DeepMind AI lab made history by defeating a champion player of the board game Go. Now Demis Hassabis, DeepMind’s cofounder and CEO, says his engineers are using techniques from AlphaGo to make an AI system dubbed Gemini that will be more capable than that behind OpenAI’s ChatGPT.
DeepMind’s Gemini, which is still in development, is a large language model that works with text and is similar in nature to GPT-4, which powers ChatGPT. But Hassabis says his team will combine that technology with techniques used in AlphaGo, aiming to give the system new capabilities such as planning or the ability to solve problems.
“At a high level you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models,” Hassabis says. “We also have some new innovations that are going to be pretty interesting.” Gemini was first teased at Google’s developer conference last month, when the company announced a raft of new AI projects. — Read More
Tag Archives: ChatBots
Inflection debuts its own foundation AI model to rival Google and OpenAI LLMs
Inflection, a well-funded AI startup aiming to create “personal AI for everyone,” has taken the wraps off the large language model powering its Pi conversational agent. It’s hard to evaluate the quality of these things in any way, let alone objectively and systematically, but a little competition is a good thing.
Inflection-1, as the model is called, is of roughly GPT-3.5 (AKA ChatGPT) size and capabilities — as measured in the computing power used to train them. The company claims that it’s competitive or superior with other models on this tier, backing it up with a “technical memo” describing some benchmarks it ran on its model, GPT-3.5, LLaMA, Chinchilla and PaLM-540B. — Read More
Run open-source LLMs on your computer. Works offline. Zero configuration.
GPT-4 Can Use Tools Now—That’s a Big Deal
… Earlier this week, OpenAI built tool use right into the GPT API with an update called function calling. It’s a little like a child’s ability to ask their parents to help them with a task that they know they can’t do on their own. Except in this case, instead of parents, GPT can call out to external code, databases, or other APIs when it needs to.
Each function in function calling represents a tool that a GPT model can use when necessary, and GPT gets to decide which ones it wants to use and when. This instantly upgrades GPT capabilities—not because it can now do every task perfectly—but because it now knows how to ask for what it wants and get it. — Read More
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models
We investigate the potential implications of large language models (LLMs), such as Generative Pre-trained Transformers (GPTs), on the U.S. labor market, focusing on the increased capabilities arising from LLM-powered software compared to LLMs on their own. Using a new rubric, we assess occupations based on their alignment with LLM capabilities, integrating both human expertise and GPT-4 classifications. Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19% of workers may see at least 50% of their tasks impacted. We do not make predictions about the development or adoption timeline of such LLMs. The projected effects span all wage levels, with higher-income jobs potentially facing greater exposure to LLM capabilities and LLM-powered software. Significantly, these impacts are not restricted to industries with higher recent productivity growth. Our analysis suggests that, with access to an LLM, about 15% of all worker tasks in the US could be completed significantly faster at the same level of quality. When incorporating software and tooling built on top of LLMs, this share increases to between 47 and 56% of all tasks. This finding implies that LLM-powered software will have a substantial effect on scaling the economic impacts of the underlying models. We conclude that LLMs such as GPTs exhibit traits of general-purpose technologies, indicating that they could have considerable economic, social, and policy implications. — Read More
#strategy, #chatbotsHundreds attend church service generated by ChatGPT
The artificial intelligence chatbot asked the believers in the fully packed St. Paul’s church in the Bavarian town of Fuerth to rise from the pews and praise the Lord.
The ChatGPT chatbot, personified by an avatar of a bearded Black man on a huge screen above the altar, then began preaching to the more than 300 people who had shown up on Friday morning for an experimental Lutheran church service almost entirely generated by AI. — Read More
RedPajama 7B now available, instruct model outperforms all open 7B models on HELM benchmarks
The RedPajama project aims to create a set of leading open-source models and to rigorously understand the ingredients that yield good performance. In April we released the RedPajama base dataset based on the LLaMA paper, which has worked to kindle rapid innovation in open-source AI.
The 5 terabyte dataset has been downloaded thousands of times and used to train over 100 models! — Read More
Falcon: New Open Source LLMs
An Elo Style Leaderboard for Language Models
We use the Elo rating system to calculate the relative performance of the models. Elo is a method for calculating the relative skill levels of players in zero-sum games, which was invented as an improved chess-rating system. The difference in the ratings between two models serves as a predictor of the model’s relative performance.You can view the voting data, basic analyses, and calculation procedure in this notebook. We will periodically release new leaderboards. — Read More
You can compare models’ relative performance for yourself, or add new models, here.
MEGABYTE, Meta AI’s New Revolutionary Model Architecture, Explained
Unlocking the true potential of content generation in natural language processing (NLP) has always been a challenge. Traditional models struggle with long sequences, scalability, and sluggish generation speed.
But fear not, as Meta AI brings forth MEGABYTE – a groundbreaking model architecture that revolutionizes content generation. In this blog, we will dive deep into the secrets behind MEGABYTE’s potential, its innovative features, and how it tackles the limitations of current approaches. — Read More
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