News from the AI & ML world
DeeperML - #agi
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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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@Latest news
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Meta CEO Mark Zuckerberg is spearheading a new initiative to develop artificial general intelligence (AGI), recruiting top AI researchers to form an elite team. This push aims to create AI systems capable of performing any intellectual task that a human can, positioning Meta to compete directly with tech giants like Google and OpenAI. Zuckerberg's involvement includes personal recruitment efforts, indicating the high priority Meta is placing on this project. This signals a significant shift for Meta, aiming to lead in the rapidly evolving AI landscape.
Disappointment with the performance of Meta's LLaMA 4 model compared to competitors like OpenAI's GPT-4 and Google's Gemini spurred Zuckerberg's increased focus on AGI. Internally, LLaMA 4 was considered inadequate in real-world user experience, lacking coherence and usability. Furthermore, Meta's metaverse investments have not yielded the anticipated results, leading the company to redirect its focus and resources toward AI, aiming to recapture relevance and mindshare in the tech industry. With tens of billions already invested in infrastructure and foundational models, Meta is now fully committed to achieving AGI. To further bolster its AI ambitions, Meta is investing heavily in AI start-up Scale AI. Meta has invested €12 billion and acquired a 49% stake in Scale AI. The investment has caused Google to end its $200 million partnership with Scale AI. Zuckerberg has also offered large salaries to poach AI talent. This move is part of Meta's broader strategy to build superintelligence and challenge the dominance of other AI leaders. Meta's aggressive pursuit of AI talent and strategic investments highlight its determination to become a frontrunner in the race to build AGI. Recommended read:
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Aminu Abdullahi@eWEEK
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Google has unveiled significant advancements in its AI-driven media generation capabilities at Google I/O 2025, showcasing updates to Veo, Imagen, and Flow. The updates highlight Google's commitment to pushing the boundaries of AI in video and image creation, providing creators with new and powerful tools. A key highlight is the introduction of Veo 3, the first video generation model with integrated audio capabilities, addressing a significant challenge in AI-generated media by enabling synchronized audio creation for videos.
Veo 3 allows users to generate high-quality visuals with synchronized audio, including ambient sounds, dialogue, and environmental noise. According to Google, the model excels at understanding complex prompts, bringing short stories to life in video format with realistic physics and accurate lip-syncing. Veo 3 is currently available to Ultra subscribers in the US through the Gemini app and Flow platform, as well as to enterprise users via Vertex AI, demonstrating Google’s intent to democratize AI-driven content creation across different user segments. In addition to Veo 3, Google has launched Imagen 4 and Flow, an AI filmmaking tool, alongside major updates to Veo 2. Veo 2 is receiving enhancements with filmmaker-focused features, including the use of images as references for character and scene consistency, precise camera controls, outpainting capabilities, and object manipulation tools. Flow integrates the Veo, Imagen, and Gemini models into a comprehensive platform allowing creators to manage story elements and create content with natural language narratives, making it easier than ever to bring creative visions to life. Recommended read:
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@Google DeepMind Blog
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Google DeepMind has introduced AlphaEvolve, a revolutionary AI coding agent designed to autonomously discover innovative algorithms and scientific solutions. This groundbreaking research, detailed in the paper "AlphaEvolve: A Coding Agent for Scientific and Algorithmic Discovery," represents a significant step towards achieving Artificial General Intelligence (AGI) and potentially even Artificial Superintelligence (ASI). AlphaEvolve distinguishes itself through its evolutionary approach, where it autonomously generates, evaluates, and refines code across generations, rather than relying on static fine-tuning or human-labeled datasets. AlphaEvolve combines Google’s Gemini Flash, Gemini Pro, and automated evaluation metrics.
AlphaEvolve operates using an evolutionary pipeline powered by large language models (LLMs). This pipeline doesn't just generate outputs—it mutates, evaluates, selects, and improves code across generations. The system begins with an initial program and iteratively refines it by introducing carefully structured changes. These changes take the form of LLM-generated diffs—code modifications suggested by a language model based on prior examples and explicit instructions. A diff in software engineering refers to the difference between two versions of a file, typically highlighting lines to be removed or replaced. Google's AlphaEvolve is not merely another code generator, but a system that generates and evolves code, allowing it to discover new algorithms. This innovation has already demonstrated its potential by shattering a 56-year-old record in matrix multiplication, a core component of many machine learning workloads. Additionally, AlphaEvolve has reclaimed 0.7% of compute capacity across Google's global data centers, showcasing its efficiency and cost-effectiveness. AlphaEvolve imagined as a genetic algorithm coupled to a large language model. Recommended read:
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