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Today:

• Experts Predict Imminent Artificial General Intelligence

• OpenAI Launches New Robotics Team

• UC Berkeley Releases Affordable Sky-T1

• Zuckerberg, Meta Linked to Pirated Books

• DeepMind Benchmark Targets LLM Hallucinations

• Hugging Face Settles FriendliAI Lawsuit

AGI and the "Age of Human Disempowerment"

Many AI experts believe we’ve reached or soon will reach Artificial General Intelligence (AGI). Sam Altman defines AGI as AI matching skilled humans in key jobs. A key concern is AI replacing human labor, shifting power to capital and reducing society’s focus on humans.

This could lead to static societies with entrenched power. Solutions like universal basic income and taxing capital are suggested to ensure fair wealth distribution and maintain human influence.

WATCH THE VIDEO ON YOUTUBE

OpenAI Launches New Robotics Team

OpenAI is expanding into robotics, hiring for hardware-focused roles like electrical and mechanical engineers and project managers. Led by Caitlin Kalinowski, formerly of Meta, the robotics team aims to develop general-purpose robots integrating advanced AI and hardware. Collaborations with Jony Ive and robotics startup Figure underscore their commitment. This marks OpenAI’s most significant push into robotics, signaling potential competition with Figure and deepening its innovation efforts beyond software.

UC Berkeley Releases Affordable Sky-T1

Researchers at UC Berkeley's Sky Computing Lab have unveiled Sky-T1, an open-source reasoning AI model that costs under $450 to train, a significant drop from the previous multimillion-dollar range. Using synthetic data and optimized techniques, Sky-T1 competes with OpenAI’s earlier models in benchmarks like coding and math but falls short in advanced sciences. This breakthrough underscores the potential for affordable, high-performing AI accessible to researchers worldwide.

Zuckerberg, Meta Linked to Pirated Books

Mark Zuckerberg is accused of approving Meta’s use of the pirated LibGen dataset to train AI models, despite internal warnings of legal risks. Authors, including Sarah Silverman, allege copyright infringement in a US court filing, claiming Meta misused their books for its Llama AI model. While a judge dismissed some claims, the case highlights the legal and ethical challenges of using copyrighted material in AI training.

DeepMind Benchmark Targets LLM Hallucinations

Google DeepMind introduced FACTS Grounding, a benchmark to improve the factual accuracy of large language models (LLMs) by evaluating their responses against detailed, long-form documents. The benchmark includes a leaderboard, led by Gemini 2.0 Flash, and uses LLMs as judges to score outputs. FACTS aims to address challenges like hallucinations and vague answers, marking a step toward enhancing LLM reliability in complex, real-world applications.

Hugging Face Settles FriendliAI Lawsuit

Hugging Face has settled a lawsuit with Korean AI startup FriendliAI over alleged patent infringement involving batching technology for AI systems. The two companies reached a confidential agreement, dismissing the case with prejudice. FriendliAI had claimed that Hugging Face’s Text Generation Inference tool violated its patented method for batching data requests. Hugging Face, a major AI platform backed by companies like Google and Nvidia, declined to comment on the settlement.

🧠RESEARCH

The FACTS Grounding Leaderboard: Benchmarking LLMs’ Ability to Ground Responses to Long-Form Input

The FACTS Grounding Leaderboard evaluates language models on their ability to generate accurate, context-based responses to long user prompts. By comparing answers to provided documents, it ensures factual correctness. Using automated judges and maintaining public and private sections, the leaderboard is available on Kaggle for continuous participation.

The GAN is dead; long live the GAN! A Modern GAN Baseline

The paper challenges the notion that GANs are inherently difficult to train, introducing a principled approach with a new regularized relativistic GAN loss. This eliminates the need for empirical tricks and outdated architectures. The minimalist R3GAN baseline outperforms StyleGAN2 and achieves competitive results on major datasets, simplifying GAN training.

Enhancing Human-Like Responses in Large Language Models

The study examines techniques to make large language models more human-like by improving language understanding, conversational coherence, and emotional intelligence. Using fine-tuning, psychological principles, and human reasoning patterns, the research enhances user interactions and expands AI applications. Future work will explore ethical concerns and biases arising from these advancements.

An Empirical Study of Autoregressive Pre-training from Videos

This study investigates autoregressive pre-training from videos using the Toto models, which treat videos as sequences of visual tokens. Trained on over 1 trillion tokens, Toto demonstrates strong performance in tasks like video classification and object tracking. Scaling reveals parallels with language models, highlighting its potential for diverse visual applications.

SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution

SWE-Fixer, an open-source LLM designed for resolving GitHub issues effectively and transparently. It integrates a retrieval module for identifying relevant code files and an editing module for generating patches. Trained on a 110K-issue dataset, SWE-Fixer achieves state-of-the-art results on open benchmarks, enhancing accessibility in software engineering tasks.

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📲SOCIAL MEDIA

🗞️MORE NEWS

• Digital creators are selling unused video footage to AI companies like OpenAI and Google for training algorithms, diversifying income while ensuring compensation and protection through licensing deals, amid rising concerns over intellectual property misuse.

• Hewlett Packard Enterprise secured a $1 billion AI server deal with Elon Musk’s X, boosting its AI business and partnerships. The deal underscores AI's growing market, with Advizex projecting significant opportunities ahead.

• Google Cloud unveiled generative AI tools at NRF 2025 to help retailers personalize shopping, streamline operations, and improve product discovery. Partners like Wayfair and NVIDIA showcase enhanced efficiency, sustainability, and customer experiences through AI advancements.

• Researchers at Beijing University introduced AgentRefine, a method inspired by Dungeons & Dragons to enhance AI agents’ adaptability and self-correction. By simulating diverse scenarios, agents improved performance on unfamiliar tasks, promoting robust decision-making and flexibility.

• Microsoft filed a lawsuit accusing a group of stealing Azure OpenAI API keys to bypass safety measures and develop tools enabling unauthorized AI use. Microsoft seeks damages, injunctive relief, and has implemented countermeasures.