News from the AI & ML world
DeeperML - #llama
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Ali Azhar@AIwire
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AIwire
Meta has announced the creation of Meta Superintelligence Labs (MSL), a new division focused on long-horizon goals and foundational AI development. This strategic move consolidates Meta's core AI efforts, bringing together the Fundamental Artificial Intelligence Research (FAIR) group, the LLaMA model team, and key infrastructure units into a single entity. The lab aims to pursue the next generation of AI systems with greater focus and resources, signaling Meta's ambition to be a leader in artificial general intelligence (AGI). Alexandr Wang, former CEO of Scale AI, has been appointed as Meta's first Chief AI Officer and will co-lead MSL's research and product direction alongside Nat Friedman, former GitHub CEO. Meta is making substantial investments in compute infrastructure, including a large-scale facility equipped with over 1.3 million Nvidia GPUs, underscoring its commitment to advancing AI capabilities.
The formation of MSL represents a significant shift in Meta's AI strategy, moving from developing AI tools for short-term product features to concentrating on foundational advancements and scientific leadership. This reorganization suggests that Meta views superintelligence not as a distant aspiration, but as a near-term opportunity. Meta has been actively recruiting top AI talent, including key figures from competitors like Apple, highlighting a competitive landscape for AI expertise. The company's investment in infrastructure and its aggressive hiring strategy indicate a strong determination to lead in the rapidly evolving AI field. In parallel with its AI research focus, Meta is also involved in initiatives to foster AI talent and its application for public good. The company is backing a £1 million 'Open Source AI Fellowship' in collaboration with the UK Government and the Alan Turing Institute. This program aims to embed AI experts within UK government departments to develop advanced tools for public services, utilizing open-source models such as Meta's Llama. This initiative demonstrates Meta's commitment to supporting the development of AI for societal benefit, alongside its ambitious internal research objectives. Recommended read:
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@ComputerWeekly.com
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Meta and the UK Government have joined forces to launch a £1 million ‘Open Source AI Fellowship’ program. The goal is to embed some of the UK’s most promising AI experts within Whitehall, the UK government's administrative center, to develop advanced AI tools. These tools will aim to improve government agility and contribute to the delivery of the Plan for Change. The Alan Turing Institute is also backing the fellowship.
The program intends to harness the power of open source AI models, including Meta's Llama models. These models have shown great potential for scientific and medical breakthroughs and could transform public service delivery. Fellows will work within government departments, potentially contributing to high-security use cases like AI-powered language translation for national security, or speeding up the approval process for house building by leveraging construction planning data. The fellowship is a practical response to the growing demand for generative AI talent. It will provide engineers a chance to address high-impact public sector challenges, which aims to create transparent, sovereign AI infrastructure that can scale across departments while reducing costs and enhancing productivity. Technology Secretary Peter Kyle emphasizes the aim is to create open, practical AI tools "built for public good," focusing on delivery rather than just ideas and developing sovereign capabilities in areas like national security and critical infrastructure. Recommended read:
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Chris McKay@Maginative
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Meta is making a significant move in the artificial intelligence race, investing $14.3 billion for a 49% stake in data-labeling startup Scale AI. This deal is more than just a financial investment; it brings Scale AI's CEO, 28-year-old Alexandr Wang, into Meta to lead a new "superintelligence" lab. The move highlights Meta's ambition to develop AI that surpasses human capabilities across multiple domains and is a calculated gamble to regain momentum in the competitive AI landscape. Meta is aiming for an AI reset and hopes that Scale's Wang is the right partner.
This acquisition reflects Meta's strategic shift towards building partnerships and leveraging external talent. Scale AI isn't a well-known name to the general public, but it's a vital component in the AI industry, providing the labeled training data that powers many AI systems, including those used by OpenAI, Microsoft, Google, and even the U.S. Department of Defense. Meta has agreed to dramatically increase its spending with Scale, but one person said Scale expects some other companies like Google and OpenAI will stop using Scale's services for fear of Meta using information about their usage to gain a competitive advantage. The "superintelligence" lab is part of a larger reorganization of Meta's AI divisions, aimed at sharpening the company's focus after facing internal challenges and criticism over its AI product releases. Meta, under CEO Mark Zuckerberg, has been heavily investing in AI infrastructure and product development since the rise of ChatGPT, launching its own large language model family, Llama. Zuckerberg has been personally recruiting top researchers to boost its AI efforts. The new lab will focus on developing a theoretical form of AI that surpasses human cognitive capabilities, a long-term and highly speculative goal that Meta is now seriously pursuing. Recommended read:
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@Latest news
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Meta has made a significant move in the artificial intelligence race by acquiring a 49% stake in data-labeling startup Scale AI for a staggering $14.3 billion. This investment values Scale AI at over $29 billion and brings Scale AI's founder and CEO, Alexandr Wang, on board to lead a new "superintelligence" lab within Meta. The move underscores Meta's determination to accelerate its AI development and compete more effectively with industry leaders like OpenAI and Google.
This strategic acquisition signifies a shift in Meta's approach to AI development, where Zuckerberg has been personally recruiting top researchers from other companies. Scale AI, while not widely known to the public, plays a crucial role in the AI ecosystem by providing the labeled training data that powers large language models. They have a global workforce of over 200,000 contractors to label various forms of data. By bringing Wang and a portion of his team in-house, Meta aims to gain a competitive edge in building AI models that surpass human capabilities. Wang, who founded Scale AI in 2016 after dropping out of MIT, has grown the company into a major player in the AI industry. Scale AI works with business, governments and labs to exploit the benefits of artificial intelligence, and has a client list that includes OpenAI, Microsoft, Meta, Google, and the U.S. Department of Defense. As Wang departs for Meta, Jason Droege, former Uber Eats founder and current Chief Strategy Officer will step in as interim CEO to ensure that Scale AI continues to operate independently despite Meta's significant stake. Recommended read:
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@www.eweek.com
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Meta is making a significant move into military technology, partnering with Anduril Industries to develop augmented and virtual reality (XR) devices for the U.S. Army. This collaboration reunites Meta with Palmer Luckey, the founder of Oculus who was previously fired from the company. The initiative aims to provide soldiers with enhanced situational awareness on the battlefield through advanced perception capabilities and AI-enabled combat tools. The devices, potentially named EagleEye, will integrate Meta's Llama AI models with Anduril's Lattice system to deliver real-time data and improve operational coordination.
The new XR headsets are designed to support real-time threat detection, such as identifying approaching drones or concealed enemy positions. They will also provide interfaces for operating AI-powered weapon systems. Anduril states that the project will save the U.S. military billions of dollars by using high-performance components and technology originally developed for commercial use. The partnership reflects a broader trend of Meta aligning more closely with national security interests. In related news, Meta's research team has made a surprising discovery that shorter reasoning chains can significantly improve AI accuracy. A study released by Meta and The Hebrew University of Jerusalem found that AI models achieve 34.5% better accuracy when using shorter reasoning processes. This challenges the conventional belief that longer, more complex reasoning chains lead to better results. The researchers developed a new method called "short-m@k," which runs multiple reasoning attempts in parallel, halting computation once the first few processes are complete and selecting the final answer through majority voting. This method could reduce computing costs by up to 40% while maintaining performance levels. Recommended read:
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@www.marktechpost.com
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Meta is making significant strides in the AI landscape, highlighted by the release of Llama Prompt Ops, a Python package aimed at streamlining prompt adaptation for Llama models. This open-source tool helps developers enhance prompt effectiveness by transforming inputs to better suit Llama-based LLMs, addressing the challenge of inconsistent performance across different AI models. Llama Prompt Ops facilitates smoother cross-model prompt migration and improves performance and reliability, featuring a transformation pipeline for systematic prompt optimization.
Meanwhile, Meta is expanding its AI strategy with the launch of a standalone Meta AI app, powered by Llama 4, to compete with rivals like Microsoft’s Copilot and ChatGPT. This app is designed to function as a general-purpose chatbot and a replacement for the “Meta View” app used with Meta Ray-Ban glasses, integrating a social component with a public feed showcasing user interactions with the AI. Meta also previewed its Llama API, designed to simplify the integration of its Llama models into third-party products, attracting AI developers with an open-weight model that supports modular, specialized applications. However, Meta's AI advancements are facing legal challenges, as a US judge is questioning the company's claim that training AI on copyrighted books constitutes fair use. The case, focusing on Meta's Llama model, involves training data including works by Sarah Silverman. The judge raised concerns that using copyrighted material to create a product capable of producing an infinite number of competing products could undermine the market for original works, potentially obligating Meta to pay licenses to copyright holders. Recommended read:
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