Latest AI News
Nvidia Introduces NemoClaw, an AI Stack to Make OpenClaw Agents More Secure
Nvidia introduced NemoClaw, an artificial intelligence (AI)-powered stack for the OpenClaw agents, on Monday. The announcement was made at the company's annual GPU Technology Conference (GTC) during the keynote session. NemoClaw essentially adds privacy and security guardrails to OpenClaw's AI agents, making them deployable and scalable for enterprises. The Santa Clara, California-based tech giant highlighted that the AI stack can be installed with a single command and is platform and agent agnostic. NemoClaw is currently available for developers and enterprises in preview.
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OpenAI Courts Private Equity to Join Enterprise AI Venture, Sources Say
OpenAI is in advanced talks with private equity firms including TPG, Advent International, Bain Capital and Brookfield Asset Management to form a joint venture that would distribute its enterprise products across the firms' portfolio companies and beyond, four people familiar with the matter said.
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Picsart now allows creators to ‘hire’ AI assistants through agent marketplace
The AI-powered design platform Picsart is launching anAI agentmarketplace, allowing creators to “hire” AI assistants to help them with specific tasks, like resizing and remixing social content, or editing product photos on Shopify. With over 130 million worldwide users that skew Gen Z, Picsart is like a more advanced Canva for social media managers and content creators. The company reachedunicorn statusamid thecreator economy boomin 2021, but has remained relevant by continuing to ramp up its AI-powered products to serve the current market. The timing is good for Picsart to launch such a marketplace, since viral projects likeOpenClawhave fueled industry demand for agentic AI chatbots that can carry out requests like a personal assistant. “Creators have been stuck as the operator of every workflow — the one doing, not deciding,” said Hovhannes Avoyan, Picsart founder and CEO, in a statement. “Our Agents change that relationship — you set direction, the agent builds a plan using real data, you approve, it executes. Picsart says that it will introduce more specialized agents each week, but to start, creators can work with four different agents: Flair, Resize Pro, Remix, and Swap. The Flair agent is perhaps the most sophisticated of the bunch, integrating with Shopify to act as an assistant for online store owners. The agent analyzes market trends to make recommendations for how a shop could improve, like suggesting it edit product photos to look more cohesive. In a future update, Flair will be able to run A/B tests and identify underperforming products to proactively offer recommendations for how a creator can improve their sales. The Resize Pro agent can resize images and videos for the recommended dimensions on various different platforms, but it uses AI to generatively extend the frame if the original media isn’t conducive to a certain size. The AI supposedly will ensure that resized images look like they were composed intentionally and weren’t just cropped haphazardly. The Remix agent invites the creator to describe a style, like “vintage film,” “watercolor,” or “cyberpunk” and edit an existing photo library to fit within that theme, while the agent feature allows users to change the backgrounds of photos in bulk. For an agent like Flair, which is supposed to work behind the scenes asynchronously to analyze store data, it will be especially helpful that users can chat with these agents on WhatsApp or Telegram. Picsart integrates with those apps specifically since their APIs enable businesses to set up AI chatbots; but as more platforms add similar tools, the functionality could broaden. “As agents extend to messaging apps creators already use, that conversation happens anywhere — at your desk or from the subway,” added Avoyan. In some cases, AI agents can prove problematic, since any LLM-based software has the potential to hallucinate and could potentiallytake actionsthat the creator did not intend. But Picsart allows users to set “autonomy levels” for agents like Flair, which give the option of requiring creator approval before taking any action. These agents should also be less vulnerable toprompt injection attacksthan more public facing agents, assuming that Picsart doesn’t roll out agents that interact more directly with customers or the internet at large. Like many other AI tools, Picsart offers a free plan with just a few AI credits each week, but users can get significantly more capacity when paying for premium subscriptions, which start at about $10 per month when billed annually. To use an AI agent, you’ll probably need a paid plan.
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NVIDIA’s 7-Chip Vera Rubin Platform in Full Production, Company Materialises Groq Deal
“Vera Rubin is a generational leap — seven breakthrough chips, five racks, one giant supercomputer,” said Jensen Huang.
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OpenAI in Talks with Private Equity Firms to Form $10 Bn Joint Venture
The company’s enterprise business has reached an annualised revenue of about $10 billion.
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The Forces Pushing Automobile GCCs in India Towards Digital Reinvention
Nearly 20% of these centres have been established in just the last three years, reflecting strong industry momentum.
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Andrew Ng Builds a Stack Overflow for AI Coding Agents
Chub is designed for your coding agent to use (not for you to use!).”
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Yotta, Gorilla Technologies Sign AI Infrastructure Deal Expected to Generate $500 Mn
Under the agreement, Yotta Data Services will operate 640 high-performance servers with more than 5,000 GPUs for AI workloads.
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TCS Launches Rapid Outcome AI Platform With NVIDIA to Fast-Track Enterprise AI Adoption
The new platform blends generative, predictive and vision AI to move enterprises from pilots to production at scale.
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Adobe, NVIDIA Partner to Develop Next-Gen Firefly Models for Creative Marketing
Adobe and NVIDIA will focus on developing next-generation Adobe Firefly models.
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LTM Ties Up With IIT Kharagpur for Demand-Led AI Skilling of Workforce
Partnership combines training and research to build project-aligned AI capabilities across teams.
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Memories AI is building the visual memory layer for wearables and robotics
Shawn Shen believes that AI will need to remember what it sees in order to succeed in the physical world. Shen’s companyMemories.aiis using Nvidia AI tools to build the infrastructure for wearables and robotics to be able to remember and recall visual memories. Memories.ai announced a collaboration with semiconductor giant Nvidia at its GTC conference on Monday. Through this partnership, Memories.ai uses Nvidia’s Cosmos-Reason 2, a reasoning vision language model, and Nvidia Metropolis, an application for video search and summarization, to continue to develop its visual memory technology. Shen (pictured above left) told TechCrunch that he and his co-founder and CTO, Ben Zhou (pictured above right), got the idea for the company while building the AI system behind Meta’s Ray-Ban glasses. Building the AI glasses got them thinking about how people would actually use the tech in real life if users couldn’t recall the video data they were recording. They looked around to see if they could find anyone already building that type of visual memory solution for AI. When they couldn’t, they decided to spin out of Meta and build it themselves. “AI is already doing really well in the digital world. What about the physical world?” Shen said. “AI wearables, robotics need memories as well. … Ultimately, you need AI to have visual memories. We believe in that future.” The ability for AI systems to remember, in general, is relatively new.OpenAI updated ChatGPT to start to remember past chats in 2024andfine-tuned that feature in 2025.Elon Musk’s xAIandGoogle Geminihave also launched their own memory tools in the past two years. But these advancements have largely focused on text-based memory, Shen said. Text-based memory is much more structured and easier to index but isn’t as helpful for physical AI applications that largely interact with the world through sight and visuals. Memories.ai was launched in 2024 and has raised $16 million thus far, through an $8 million seed round in July 2025 and an $8 million extension. The round was led by Susa Ventures and included Seedcamp, Fusion Fund, and Crane Venture Partners, among others. Shen said successfully building this visual memory layer required two things: building the infrastructure needed to embed and index videos into a data format that can be stored and recalled, and capturing the data needed to train the model to do just that. The company launched itslarge visual memory model (LVMM) in July 2025. Shen said it could be compared to a smaller version ofGemini Embedding 2, a multimodal indexing and retrieving model, that was released earlier this month. For data collection, the company created LUCI, a hardware device worn by the company’s “data collectors” that records video used to train the model. Shen said they don’t plan to become a hardware company, nor sell these devices, but, rather, that they built their own because they weren’t satisfied with off-the-shelf video recorders that focused on high-definition and battery-eating video formats. The company released the second generation of this LVMM and signed apartnership with Qualcommto run on Qualcomm’s processors starting later this year. Memories.ai is also working with some of the large wearable companies already, Shen said, but declined to disclose which ones. Despite some demand now, Shen sees even bigger opportunities in wearables and robotics yet to come. “In terms of commercialization, we are more focused on the model and the infrastructure, because ultimately we think the wearables and robotics market will come, but it’s probably just not now,” Shen said.
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