Foundational

As generative artificial intelligence (AI) products like OpenAI's ChatGPT and Google's Gemini become ubiquitous, India will develop its own foundational models, minister of state for electronics and IT Rajeev Chandrasekhar said."We will be developing our own Indian foundational models. The world is talking about ChatGPT and OpenAI. Based on our own languages and our own India data sets, we expect that as a consequence of India's AI mission, we will have sovereign AI models that are designed and built in India," the…

Grand Cayman, Cayman Islands, March 5th, 2024, ChainwireSui is one of twelve networks that will be integrated at ZettaBlock’s Open Beta launch, giving builders seamless access to a powerful new source of Web3 data platformSui, the lightning fast, infinitely horizontally scalable layer 1 blockchain that has quickly become a leading destination for DeFi activity, has been announced by data platform ZettaBlock as one of the protocols chosen to be a foundational integration partner at the launch of its…

Integrating Innovations in Continual Learning Advancements Towards Artificial General Intelligence (AGI), Including VOYAGER, DEPS, and AutoGPT.Authors: Elahe Aghapour, Salar RahiliIntroduction:In the past decade and especially with the success of deep learning, an ongoing discussion has formed around the possibility of building an Artificial General Intelligence (AGI). The ultimate goal in AGI is to create an agent that is able to perform any task that a human being is capable of. A core capability required for such an…

What works, the pros and cons, and example code for each approachIf some of the terminology I use here is unfamiliar, I encourage you to read my earlier article on LLMs first.There are teams that are employing ChatGPT or its competitors (Anthropic, Google’s Flan T5 or PaLM, Meta’s LLaMA, Cohere, AI21Labs, etc.) for real rather for cutesy demos. Unfortunately, informative content about how they are doing so is lost amidst marketing hype and technical jargon. Therefore, I see folks who are getting started with generative AI…

Despite their ability to crank out incredibly lifelike prose, generative AIs like Google's Bard or OpenAI's ChatGPT (powered by GPT-4), have already shown the current limitations of gen-AI technology as well as their own tenuous grasp of the facts — arguing that the JWST was the first telescope to image an exoplanet, and that Elvis' dad was an actor. But with this much market share at stake, what are a few misquoted facts against getting their product into the hands of consumers as quickly as possible?  The team over at…

Road to Reinforcement LearningCover photo generated by the author using an AI tool Midjourney (Licenses as Creative Commons Noncommercial 4.0 asset license)Through the previous two articles: (1) Markov States, Markov Chain, and Markov Decision Process, and (2) Solving Markov Decision Process, I set up a foundation for developing a detailed concept of reinforcement learning (RL). The RL problem is formulated as Markov Decision Process (MDP) which can be solved for optimal policies (i.e. what action needs to be taken by an…

Road to Reinforcement LearningCover photo generated by the author using an AI tool Dreamstudio (Licenses as https://creativecommons.org/publicdomain/zero/1.0/)In the first part, I discussed some basic concepts to establish a foundation for reinforcement learning (RL) such as Markov states, the Markov chain, and the Markov decision process (MDP). Reinforcement learning problems are built on top of MDP.An MDP is a 4-tuple model (𝓢, 𝓐, 𝓟, 𝓡) where s ∈ 𝓢 is a state, a ∈ 𝓐 is an action taken while an agent is a state s, 𝓟(s’ |…

Road to Reinforcement LearningCover photo generated by the author using an AI tool Dreamstudio (Licenses as https://creativecommons.org/publicdomain/zero/1.0/)Reinforcement learning (RL) is a type of machine learning in which an agent learns to interact with its environment by trial and error in order to maximize a reward. It is different from supervised learning, in which an agent is trained on labeled examples, and unsupervised learning, in which an agent learns to identify patterns in unlabeled data. In reinforcement…