Recently, OpenAI, in collaboration with the nonprofit organization Common Sense Media, launched a free training course on artificial intelligence (AI) designed to help teachers understand AI technologies and prompt engineering. This new initiative was officially released on Wednesday, aiming to provide educators with the skills and resources to effectively and responsibly integrate AI tools into the classroom. Image source note: Image generated by AI, image licensed from provider Midjourney.

The New York Times and the Daily News encountered an unexpected twist in their copyright lawsuit: an OpenAI engineer inadvertently deleted virtual machine search data that could have been key evidence, adding a dramatic turn to this high-profile legal dispute. According to a letter submitted to the U.S. District Court for the Southern District of New York on Wednesday night, lawyers and technical experts for the two media companies had previously invested over 150 hours searching OpenAI's AI training dataset. However, on November 14, an OpenAI engineer accidentally deleted data stored on the virtual machine.

Recently, xAI engineer Hieu Pham posted an 'explosive' message on social media claiming that xAI's large language model Grok3 had successfully proven the Riemann Hypothesis, leading to a halt in the model's training. This news quickly sparked heated discussions in the AI community, with netizens expressing shock and struggling to discern the truth. After all, the Riemann Hypothesis is one of the seven Millennium Prize Problems, hailed as the 'crown jewel' of conjectures, its difficulty is well understood. Hours later, Pham revealed in another post that it was just a joke.

On November 14, OpenAI released a professional student writing guide, systematically outlining the proper use of ChatGPT in the field of education for the first time. This guide not only addresses concerns from the education sector about AI but also provides clear action points for students on how to appropriately utilize AI tools. OpenAI emphasizes that ChatGPT should be viewed as a learning aid rather than a replacement. When used correctly, this tool can deepen the understanding of complex concepts; conversely, improper use may hinder the development of learning skills.

Recently, NVIDIA unveiled its brand-new Blackwell platform and showcased its initial performance in the MLPerf Training 4.1 benchmark tests. According to the test results, Blackwell achieved a doubling of performance in certain aspects compared to the previous Hopper platform, garnering widespread attention in the industry. In the MLPerf Training 4.1 benchmark tests, the Blackwell platform excels in LLM (Large Language Models).

Recently, a new study from the University of Michigan found that an energy-efficient method for training large language models can achieve similar results in the same amount of time while reducing energy consumption by 30%. This method can save enough energy to power 1.1 million American households by 2026. The researchers developed a software tool named Perseus that identifies the critical path, which is a series of subtasks requiring the longest time to complete. Then, Perseus reduces the processor speed on non-critical paths so that all tasks can finish simultaneously.

The Massachusetts Institute of Technology (MIT) showcased a brand new robot training model this week that abandons the previous focus on training methods centered around specific datasets, opting instead for an approach that utilizes vast amounts of information similar to that used in training large language models (LLMs). Researchers noted that imitation learning—where agents learn by mimicking individuals performing tasks—can fail when facing minor challenges. These challenges may include varying lighting conditions, different environmental setups, or new obstacles. In such cases, the robots lack sufficient data to adapt to these changes.

Large Language Models (LLMs) like GPT and Llama have sparked a revolution in the field of artificial intelligence, but efficiently training these massive models while aligning them with human values remains a challenge. Reinforcement Learning with Human Feedback (RLHF) has become an important training method for LLMs in recent years, but traditional RLHF frameworks have limitations in flexibility, efficiency, and scalability. To address these issues, the ByteDance Doubao Large Model Team has open-sourced an RLHF framework called HybridFlow.

AI video platform D-ID today announced the launch of two new virtual avatars — Express and Premium+, aimed at enhancing the quality and efficiency of content creation. More and more enterprises are looking to use more human-like AI avatars to ease the burden of video production, particularly in marketing, sales, and customer support. D-ID's new models are designed to secure a place in this competitive market. The training time for the Express avatar is approximately one minute of video.

Recently, ByteDance quietly launched an AI model sharing community called 'Lumi'. The platform integrates various functions including model sharing, workflow building, and LoRA training, although it is currently still in the internal testing phase. Product entrance: https://top.aibase.com/tool/lumi. The core highlight of Lumi is its model sharing and management features, allowing users to easily upload their developed AI models.

Opening in January 2025, Fred Fitness in Santa Monica will officially welcome guests. This gym, with its innovative AI-driven personalized workout concept, is expected to revolutionize the U.S. fitness market. Backed by the European fitness giant Clever Fit and utilizing cutting-edge EGYM technology, Fred Fitness is dedicated to providing members with tailored training plans and real-time guidance, allowing everyone to enjoy a fitness experience akin to having a personal trainer, but at a significantly lower cost.