Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, we were again watching developments in AI-powered robots and LLMs. A collaboration between Nvidia and UPenn released DrEureka, a new open-source model that uses an LLM agent to write code for training robots in simulation and then write further code to transfer to real-world deployment. Tesla also released a video update on the progress of its Optimus robot, demonstrating many robots being trained on different tasks via human teleoperation. The neural net is run end to end (meaning camera and sensor data in, joint control sequences out) and two bots have started early testing at real factory workstations. In the world of LLMs, we were impressed with Deepseek v2, a new 236bn open-source Mixture of Experts model from Deepseek — a Chinese company. The model was trained on 8.1 trillion tokens and has 21bn activated parameters. The model scores 77.8 on the MMLU benchmark and 81.1 on HumanEval. It is offered via API at $0.14/m token input and $0.28/m output. While we are often skeptical about the sustainability of API pricing (given it can be a customer acquisition cost), the model performance vs active parameters is very impressive. The company noted benefits from advances in Multi-head Latent Attention ( better attention with efficient inference) and a novel sparse architecture for reduced training costs. Perhaps the US AI chip export ban to China is having some impact on driving focus on innovations and efficiency! Separately in the LLM world this week — eyes have been on mysterious new models being tested at chat.lmsys.org; “gpt2-chatbot”, followed several days later by “im-a-good-gpt2-chatbot” and “im-also-a-good-gpt2-chatbot”. Speculation that these were new models being tested by OpenAI was fueled significantly by cryptic tweets from Sam Altman — always adept at keeping OpenAI in focus! The original GPT-2 had 1.5bn parameters — so maybe this is a hint that OpenAI is testing out a new, much smaller model (vs. GPT-4 or GPT-3). The company has been known to test out new ideas in models at a smaller scale — and use scaling laws to predict performance at a higher parameter/ training token count, so perhaps this is the case here. Why should you care? AI robotics has accelerated significantly in the past year, and now, many different teams are using very different strategies and architecture pathways to advance capabilities. While it is still very hard to predict the pace of progress from here, we think AI-powered robotics can have a huge impact and become significantly more powerful than traditional human-coded robotics. On this topic, this week, RethinkX released a thoughtful blog post on the potential impact of humanoid robots: This time, we are the horses: the disruption of labor by humanoid robots. -Louie Peters — Towards AI Co-founder and CEO This issue is brought to you thanks to Latitude.sh: Introducing Launchpad, the most powerful container GPU platform to date.Launchpad leverages every piece of hardware to launch your models, bringing an unrelenting performance that makes other container GPU tools feel just too slow. With Latitude.sh, you can fine-tune and deploy your machine learning models with hourly billing starting at $1.32/hr. Containers are provisioned on ultra-fast NVMe drives and leverage an unrestricted high-throughput network that gives you access to speeds of up to 100 Gbps. Deploy today:– NVIDIA’s L40S GPU (48GB) @ $1.32/hour– NVIDIA’s H100 Tensor Core GPU (80GB) @ $2.10/hour Scale your ML inference and fine-tuning workloads with Latitude’s Launchpad! Hottest News 1.OpenAI CEO Sam Altman Says GPT-4 Is the Dumbest AI Model You’ll Ever Have To Use Again During a recent appearance at Stanford University, OpenAI’s Sam Altman said that GPT-4 is the most rudimentary AI that users will encounter as the company progresses towards more sophisticated models like GPT-5, which is expected to feature enhanced abilities such as video generation. He foresees AI developing into highly efficient assistants that effortlessly perform tasks and provide solutions. 2. GitHub Launches Copilot Workspace GitHub has launched Copilot Workspace, a comprehensive developer environment that facilitates the entire coding process, including planning, coding, testing, and deployment, through natural language commands. This offers AI industry professionals an integrated solution for streamlining development workflows. 3. Amazon Q, a Generative AI-Powered Assistant for Businesses and Developers Amazon is doubling down on enterprise AI with the release of its AI chatbot Q. The chatbot acts as an assistant for Amazon Web Services (AWS) users, learning from a company’s data and workflows so employees can ask questions about their business. 4. A Mysterious “gpt2-Chatbot” AI Model Suddenly Appears on the LMSYS Leaderboard A mysterious AI model named gpt2-chatbot, displaying GPT-4.5-like capabilities, has emerged on lmsys.org, prompting speculation of it being an unofficial OpenAI test for their next iteration. Key identifiers such as response quality, OpenAI-specific traits, and rate limits suggest a high level of sophistication, potentially hinting at a discreet benchmarking initiative by OpenAI. 5. A ChatGPT Search Engine Is Rumored To Be Coming Next Week OpenAI is rumored to be launching a ChatGPT-based search engine, potentially at “search.chatgpt.com,” aiming to rival Google by integrating a chatbot feature with traditional search results. This reflects the industry trend of AI potentially revolutionizing standard web search methods. AI Job Listing: Startup CTO role Our friends are recruiting a CTO for a venture-backed stealth startup committed to revitalizing SMEs through digital innovation. The role is Remote and open to candidates globally. In this pivotal role, you’ll help architect the technical vision, manage the deployment of AI-powered solutions, and lead a top-tier technology team to transform SMEs. If you’re a tech leader passionate about leveraging AI to drive business success and want to help shape the future of SMEs, please reach out to denis@towardsai.net Five 5-minute reads/videos to keep you learning 1.Comparison of Llama-3 and Phi-3 using RAG This guide shares how to create a self-hosted “Chat with your Docs” application that integrates Meta AI’s Llama3 and Microsoft’s Phi3 language models into a Retrieval Augmented Generation (RAG) system. It […]
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