Category: AI News
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Tracking every decision, dollar and delay: The new process intelligence engine driving public-sector progress
[ad_1] Presented by Celonis The State of Oklahoma discovered its blind spots the hard way. In April 2023, a legislative report revealed its agencies had spent $3 billion without proper oversight. Janet Morrow, Director of Oklahoma's Risk, Assessment and Compliance Division, set out to track thousands of monthly transactions across dozens of disconnected systems. The…
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Instacart pilots agentic commerce by embedding in ChatGPT
[ad_1] Instacart has deployed an embedded checkout experience within ChatGPT through the emerging Agentic Commerce Protocol. With the deployment, the company is the first partner to launch an app on ChatGPT that offers a complete shopping cycle – from query to payment – without requiring the user to leave the conversation interface. Operationalising agentic commerce…
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From Transformers to Associative Memory, How Titans and MIRAS Rethink Long Context Modeling
[ad_1] What comes after Transformers? Google Research is proposing a new way to give sequence models usable long term memory with Titans and MIRAS, while keeping training parallel and inference close to linear. Titans is a concrete architecture that adds a deep neural memory to a Transformer style backbone. MIRAS is a general framework that…
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Why AI coding agents aren’t production-ready: Brittle context windows, broken refactors, missing operational awareness
[ad_1] Remember this Quora comment (which also became a meme)? (Source: Quora) In the pre-large language model (LLM) Stack Overflow era, the challenge was discerning which code snippets to adopt and adapt effectively. Now, while generating code has become trivially easy, the more profound challenge lies in reliably identifying and integrating high-quality, enterprise-grade code into…
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Aluminium OS is the AI-powered successor to ChromeOS
[ad_1] The convergence of mobile and desktop operating systems is a goal that has remained elusive for big tech firms since the early days of the smartphone. Microsoft’s attempt in the form of Windows Mobile was reaching the end of its road by 2010, and despite Apple’s iOS/iPadOS and macOS moving very slowly towards one…
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OpenAGI Foundation Launches Lux: A Foundation Computer Use Model that Tops Online Mind2Web with OSGym At Scale
[ad_1] How do you turn slow, manual click work across browsers and desktops into a reliable, automated system that can actually use a computer for you at scale? Lux is the latest example of computer use agents moving from research demo to infrastructure. OpenAGI Foundation team has released Lux, a foundation model that operates real…
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AI denial is becoming an enterprise risk: Why dismissing “slop” obscures real capability gains
[ad_1] Three years ago, ChatGPT was born. It amazed the world and ignited unprecedented investment and excitement in AI. Today, ChatGPT is still a toddler, but public sentiment around the AI boom has turned sharply negative. The shift began when OpenAI released GPT-5 this summer to mixed reviews, mostly from casual users who, unsurprisingly, judged…
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UK and Germany plan to commercialise quantum supercomputing
[ad_1] The UK and Germany plan to integrate their science sectors to accelerate the commercialisation of quantum supercomputing technology. Announced on the final day of the German president’s state visit, these joint commitments target the gap between R&D and enterprise application in computing, sensing, and timing. The partnership involves specific funding to fast-track product development…
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AI Interview Series #4: Transformers vs Mixture of Experts (MoE)
[ad_1] Question: MoE models contain far more parameters than Transformers, yet they can run faster at inference. How is that possible? Difference between Transformers & Mixture of Experts (MoE) Transformers and Mixture of Experts (MoE) models share the same backbone architecture—self-attention layers followed by feed-forward layers—but they differ fundamentally in how they use parameters and…
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The 'truth serum' for AI: OpenAI’s new method for training models to confess their mistakes
[ad_1] OpenAI researchers have introduced a novel method that acts as a "truth serum" for large language models (LLMs), compelling them to self-report their own misbehavior, hallucinations and policy violations. This technique, "confessions," addresses a growing concern in enterprise AI: Models can be dishonest, overstating their confidence or covering up the shortcuts they take to…