Meta is creating significant pressure for OpenAI and Google by making it's AI model available for commercial use

- Meta has unveiled Llama 3.1 405B, its largest open source AI model to date, boasting 405 billion parameters, making it competitive with leading proprietary models like OpenAI’s GPT-4o and Anthropic’s Claude 3.5 Sonnet. - Trained using 16,000 Nvidia H100 GPUs and a dataset of 15 trillion tokens, Llama 3.1 405B is designed to handle a variety of text-based tasks, from coding to summarizing documents in multiple languages. - Meta is also exploring multimodality, developing Llama models that can recognize images and videos, and understand speech, although these are not yet ready for public release. - The company has updated Llama’s license to allow developers to use outputs from the Llama 3.1 model family to develop third-party AI generative models, aiming to foster an ecosystem around its AI tools. - Despite its advancements, Llama 3.1 405B requires significant hardware to run and Meta continues to face scrutiny over its use of training data, including copyrighted materials. Source: Techcrunch

OpenAI CEO, Sam Altman testified against Congress(USA wala) and the end result seems to be there will be global regulations on AI. There might be a transparency law that dictates what Data is used for training. Now I have a few questions: 1. Is it a pro game move by OpenAI to slow down AI Training of smaller companies that are just starting out? 2. Since big tech has back door access to law makers lobby(as we saw in case if right to repair), will they bend the regulations per there liking? 3. Given countries like US and China have supremacy over AI Research, will it curtain AI Development in countries like India? 4. Will Google Bard again cry in trashcan?

Marc Andreessen famously declared, "Software is eating the World," and the truth in that statement has only grown with time. But here's the kicker: software itself is now under threat, because "Data is eating Software." The evolution of technology has reached a fascinating moment. Back in the day, individuals and organizations ran their own servers. Essentially, it was highly centralized and resource-intensive. Then came the era of Cloud Computing, which transformed computing into a utility, much like electricity. Cloud computing became widely accessible through AWS, Azure, and GCP and quickly commoditized server infrastructure. This shift enabled unparalleled scalability and flexibility, essentially democratizing access to computing power. Now, a similar transformation is underway in AI, particularly with the foundational models developed by tech companies like Meta, OpenAI, Google, and others. Here's where the ambitious vision for the future unfolds. Just as Cloud Computing commoditized servers, data is poised to commoditize foundational AI models. These models are remarkably powerful, but they will too hit an upper limit on how great they can be. As Data accumulates at an exponential rate, it's becoming clear that Data, not these foundational models, will be the only sustainable moat in any AI application. The true moat isn't the model itself; it's the data that refines and trains the model. Data will be the key to unlocking the full potential of AI, enabling personalized experiences, hyper-accurate predictions, and previously unimaginable insights. So, while Marc Andreessen's proclamation about software remains timeless, the torch is passing to "Data is eating Software."

AI is unlike any other past technology revolution. It is going to make cost of intelligence trending toward zero. Going by exponential curve of AI growth, in next 3-4 years, we are going to have an AI model which can code better than 95% of coders... Deep mind already has model Alphacode which can code better than 50% of competitive coders. People are living in fool's paradise by thinking that AI will create massive amount of job.... It won't because it will make cost of intelligence near to zero making coding, analyst, consultant, product management job redundant.... What takes 100 coders to build a product won't take more 10 coders in few years from now...

Based on experience, which one is better? Any significant new features with Meta's version?

What would happen to all the AI startups that are raising massive rounds at insane valuations once OpenAI improves GPT-4 (some spicy rumours are going around) or comes up with GPT-5? Most of these "AI" startups are just a wrapper around these existing, capable LLMs. Better versions of these LLMs would start generalising more and doing those specific functions done by these startups much better.

What is hugging face exactly? How can it be used in data science?

And remember, this is open sourced based in only 34 billion parameter.... People have no idea what they are going to witness in a year or two .... In 5 years, there will be no need of hiring most developers for insane salaries...

https://twitter.com/protosphinx/status/1639616455535632386?s=46&t=-Y8gJsKWsnMPnWZzk9ilMQ This tweet summarizes a lot of premature fear-mongering related to ChatGPT. Comment if you agree/disagree (if disagree then why)