ROBOMARKET
Stay Informed
Daily coverage from 2793 trusted sources — robotics, AI agents, and industry analysis for the GCC.
Last Updated: 10:00 AM (11m ago)
Auto-refresh every 2 hours
How NTT DATA AIVista closes the last mile of agentic AI for enterprise agents
Presented by NTT DATA AIVista At VB Transform 2026, NTT DATA AIVista CEO Bratin Saha joined VentureBeat CEO and editor-in-chief Matt Marshall to discuss the last-mile challenge of operationalizing frontier models in regulated production, where reliability, context, guardrails, and security determine whether AI delivers enterprise value. The conversation centered around the question facing every enterprise now pouring money into AI: how to convert that spending into real, tangible value. It s not just a model, you re building a system around the model, Saha said. The last mile is the work of wrapping a frontier model in an enterprise s own data, workflows, and guardrails.In the end, regulated production turns on more than just technology, Saha said. Today, most enterprise AI projects fail during implementation because of poor integration, domain specialization gaps, lack of governance, and unclear ownership of outcomes. Last-mile specialization turns a capable foundation model into an e
AI migrated legacy COBOL programs to Java, bugs included
Comments
OpenAI's super PAC is funding AI-generated news site attacking industry critics
Comments
AI poster wins Ohio State Fair contest
Comments
Unexpected events and prosocial behavior: the Batman effect
Comments
Rachika Nayar’s Heaven Come Crashing is an instrumental epic of desperate longing
Two minutes and thirty seconds into the title track of Rachika Nayar's Heaven Come Crashing, an absolutely massive drum and bass beat drops. As a fan of Nayar's debut record Our Hands Against The Dusk, it caught me off guard. That album has no percussion on it at all. Heaven Comes Crashing is almost entirely drum-free, too. There are some rapid-fire mechanical hi-hats on the second track, "Tetramorph," and the back half of track six, "Gayatri," has what sounds like a snare buried deep in the mix. But it isn't until track seven that Nayar delivers an unexpected drum explosion, before immediately retreating to the soothing wash of "Sleepless," … Read the full story at The Verge.
The global memory shortage hits the MacBook Air
The global memory chip shortage appears to be affecting the availability of Apple’s most popular Mac.
Sam Altman and AI’s decel debate
On the latest episode of Equity, we discuss why Sam Altman has calling on the industry to "pace the rate of AI development."
My personal AI benchmark: "Generate an SVG of a frog with a Habsburg jaw."
Comments
Fender’s CEO seems to think your bandmates are just analog AI
Edward “Bud” Cole speaks in Japan in 2023. | Image: Jun Sato/WireImage Fender CEO Edward "Bud" Cole gave an interview to T3 in May celebrating the 75th anniversary of the Telecaster with comments on AI and music that initially flew under the radar. But it has started making the rounds recently, pouring more fuel on an already raging fire of bad PR following the company pissing off basically the entire guitar-playing community by sending cease-and-desist letters to builders, claiming copyright of the Stratocaster body shape. Some influential guitar YouTubers have even said they're done buying Fender gear in the wake of the controversy. And Cole's resurfaced comments comparing cover songs and bandmates to a sort … Read the full story at The Verge.
Stop graphing everything: When GraphRAG actually beats vector RAG
If you have built anything with retrieval-augmented generation (RAG) in the last two years, you have lived its central frustration: You chop your documents into chunks, embed them, retrieve the top few that look similar to the question, and hand them to the model. For “What was our Q3 refund policy?” This works beautifully. For “What are the recurring themes across two years of customer complaints?” it falls flat — because no single chunk contains the answer.The fashionable fix is GraphRAG: Instead of feeding the model isolated snippets, you first build a knowledge graph of the entities and relationships in your corpus, then use that structure as context. The pitch is seductive. But seductive pitches deserve scrutiny, so I went through the evidence — the original Microsoft paper plus four independent benchmark studies — to answer a simple question: When you swap text chunks for a context graph, do answers actually get better?The short version: Yes, substantially — but only for the righ
Malaysia is reportedly shutting down Balaji Srinivasan’s Network School
Let's see how this "frontier community for techno-optimists" is doing ...