Nvidia’s growing AI arsenal now includes video search and summarization tool AI Blueprint, which helps developers build visual AI agents that analyze video and image content. The agents can answer user questions, generate summaries and even enable alerts for specific scenarios. The new feature is part of Metropolis, Nvidia’s developer toolkit for building computer vision applications using generative AI. Globally, enterprises and public organizations increasingly rely on visual information. Cameras, IoT sensors and autonomous vehicles are ingesting visual data at high rates, and visual agents can help monitor and make sense of that workflow. Continue reading Nvidia’s AI Blueprint Develops Agents to Analyze Visual Data

In its first week of public beta, Anthropic’s “Computer Use” feature is gaining immediate traction, helping people do research and complete coding tasks. Claude works autonomously in Computer Use mode, suggesting broad implications for future productivity and workforce goals. Coming on the heels of OpenAI’s Swarm framework, these early forays into independent AI assistants seem to indicate that implementing such systems will be an area of focus for businesses in 2025. Claude can “see” what’s onscreen and use its “judgment” to adapt to different tasks, segueing across workflows and software. Continue reading Anthropic’s AI Agents for Claude Sonnet Increase Productivity

Microsoft next month moves to public preview with a Copilot Studio feature that lets users create autonomous AI agents. The agents had been in private preview since the spring, and the tech giant’s move to take them public comes after Salesforce launched its own agentic program in September. Microsoft also has plans to add 10 autonomous agents to Dynamics 365, an enterprise suite geared toward resource planning and customer relationship management. Microsoft announced the news this week at its “AI Tour” event in London. Copilot is Microsoft’s branded AI assistant, while Copilot Studio lets people customize their Copilot assistants. Continue reading Microsoft Widens Copilot AI Agent Preview, Adds Templates

OpenAI has announced Swarm, an experimental framework that coordinates networks of AI agents, and true to its name the news has kicked over a hornet’s nest of contentious debate about the ethics of artificial intelligence and the future of enterprise automation. OpenAI emphasizes that Swarm is not an official product and says though it has shared the code publicly it has no intention of maintaining it. “Think of it more like a cookbook,” OpenAI engineer Shyamal Anadkat said in a social media post, calling it “code for building simple agents.” Continue reading OpenAI Tests Open-Source Framework for Autonomous Agents

Accenture is forming an internal Nvidia Business Group staffed with 30,000 global employees trained to help clients “reinvent processes and scale enterprise AI adoption with AI agents,” the consulting firm announced. Accenture will also use its AI Refinery platform to help companies customize AI models and agents using the full Nvidia AI stack including AI Foundry, AI Enterprise and Omniverse. “With generative AI demand driving $3 billion in Accenture bookings in its recently closed fiscal year, the new group will help clients lay the foundation for agentic AI functionality,” Accenture said. Continue reading Accenture Has Plans for Scaling Enterprise AI with Nvidia Unit

Meta Platforms CEO Mark Zuckerberg unveiled the latest version of computer vision platform SAM 2, an update on the company’s Segment Anything Model that automates for video what the original SAM did for still images — identifying the edges of an object and isolating it in the frame. Zuckerberg demonstrated SAM 2 as part of a SIGGRAPH 2024 keynote session in which he was interviewed by Nvidia CEO Jensen Huang. “Being able to do this in video and have it be zero shot and tell it what you want, it’s pretty cool,” Zuckerberg said. Meta is sharing the code and model weights for SAM 2 with a permissive Apache 2.0 license. Continue reading Mark Zuckerberg Unveils SAM 2 AI Tech for Segmenting Video

Deepgram’s new Aura software turns text into generative audio with a “human-like voice.” The 9-year-old voice recognition company has raised nearly $86 million to date on the strength of its Voice AI platform. Aura is an extremely low-latency text-to-speech voice AI that can be used for voice AI agents, the company says. Paired with Deepgram’s Nova-2 speech-to-text API, developers can use it to “easily (and quickly) exchange real-time information between humans and LLMs to build responsive, high-throughput AI agents and conversational AI applications,” according to Deepgram. Continue reading Deepgram’s Speech Portfolio Now Includes Human-Like Aura

Bill Gates has published his thinking about the future of computing, and fascinatingly, it’s the same as his prediction from decades ago: agents. No mere bots — and certainly not anthropomorphized paperclips — agents (to Gates) will abstract almost all HCI to a natural language conversation with systems that have our permission to take meaningful actions. Gates makes a highly specific prediction: within five years, the very idea of an app itself will seem as outdated as a rotary phone dial does next to an iPhone. A conversational UI will sit on top of a language model that has access to as much of our private data as we wish to give it. Continue reading Bill Gates Imagines Agents as the Human-Computer Interface

Nvidia Research has debuted Eureka, an AI agent that autonomously teaches robots complex motor skills. Powered by OpenAI’s GPT-4, Eureka has successfully trained a robotic hand to handle a pen with the dexterity of a human — a first, according to Nvidia. Eureka has also enabled robots to do things like open drawers, manipulate scissors and toss and catch balls, along with dozens of other tasks. “Eureka is a first step toward developing new algorithms that integrate generative and reinforcement learning methods to solve hard tasks,” according to Nvidia Senior Director of AI Research Anima Anandkumar said. Continue reading Nvidia Leverages OpenAI’s GPT-4 to Train Dexterous Robots

Google’s DeepMind division has improved the speed and performance of its machine learning system with technology whose attributes are similar to how animals are thought to dream. Dubbed “Unreal” (Unsupervised Reinforcement and Auxiliary Learning), the system learned to complete Labyrinth, a 3D maze, ten times faster than the best existing artificial intelligence software and can now play up to 87 percent of expert human players’ performance. DeepMind researchers will now be able to try out new ideas much more quickly. Continue reading Google DeepMind Speeds AI Learning with Computer Dreams