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Companies hate to admit it, but the road to production-level AI deployment is littered with proof of concepts (PoCs) that go nowhere, or failed projects that never deliver on their goals. In certain domains, there’s little tolerance for iteration, especially in something like life sciences, when the AI application is facilitating new treatments to markets …

6 proven lessons from the AI projects that broke before they scaled Read More »

AI coding, vibe coding and agentic swarm have made a dramatic and astonishing recent market entrance, with the AI Code Tools market valued at $4.8 billion and expected to grow at a 23% annual rate.  Enterprises are grappling with AI coding agents and what do about expensive human coders.  They don’t lack for advice.  OpenAI’s …

What could possibly go wrong if an enterprise replaces all its engineers with AI? Read More »

The developers of Terminal-Bench, a benchmark suite for evaluating the performance of autonomous AI agents on real-world terminal-based tasks, have released version 2.0 alongside Harbor, a new framework for testing, improving and optimizing AI agents in containerized environments. The dual release aims to address long-standing pain points in testing and optimizing AI agents, particularly those …

Terminal-Bench 2.0 launches alongside Harbor, a new framework for testing agents in containers Read More »

Researchers at New York University have developed a new architecture for diffusion models that improves the semantic representation of the images they generate. “Diffusion Transformer with Representation Autoencoders” (RAE) challenges some of the accepted norms of building diffusion models. The NYU researcher’s model is more efficient and accurate than standard diffusion models, takes advantage of …

NYU’s new AI architecture makes high-quality image generation faster and cheaper Read More »

Across industries, rising compute expenses are often cited as a barrier to AI adoption — but leading companies are finding that cost is no longer the real constraint. The tougher challenges (and the ones top of mind for many tech leaders)? Latency, flexibility and capacity. At Wonder, for instance, AI adds a mere few centers …

Ship fast, optimize later: Top AI engineers don’t care about cost — they’re prioritizing deployment Read More »

By now, enterprises understand that retrieval augmented generation (RAG) allows applications and agents to find the best, most grounded information for queries. However, typical RAG setups could be an engineering challenge and also exhibit undesirable traits.  To help solve this, Google released the File Search Tool on the Gemini API, a fully managed RAG system …

Why Google’s File Search could displace DIY RAG stacks in the enterprise Read More »

Even as concern and skepticism grows over U.S. AI startup OpenAI’s buildout strategy and high spending commitments, Chinese open source AI providers are escalating their competition and one has even caught up to OpenAI’s flagship, paid proprietary model GPT-5 in key third-party performance benchmarks with a new, free model. The Chinese AI startup Moonshot AI’s …

Moonshot’s Kimi K2 Thinking emerges as leading open source AI, outperforming GPT-5, Claude Sonnet 4.5 on key benchmarks Read More »

Integrating AI models directly into extended detection and response (XDR) platforms is delivering breakthrough improvements in SOC investigation speed and accuracy. In an exclusive interview with VentureBeat, eSentire revealed that deploying Anthropic’s Claude across their Atlas XDR Platform compresses comprehensive threat investigations from five hours to seven minutes, delivering a 43x speed improvement, while matching …

How Anthropic’s Claude cuts SOC investigation time from 5 hours to 7 minutes Read More »

Presented by Salesforce Vibe coding — the fast-growing trend of using generative AI to spin up code from plain-language prompts — is quick, creative, and great for instant prototypes. But many argue that it’s not cut out for building production-ready business apps with the security, governance, and trusted infrastructure that enterprises require. In other words, …

From prototype to production: What vibe coding tools must fix for enterprise adoption Read More »

Presented by Arm AI is no longer confined to the cloud or data centers. Increasingly, it’s running directly where data is created — in devices, sensors, and networks at the edge. This shift toward on-device intelligence is being driven by latency, privacy, and cost concerns that companies are confronting as they continue their investments in …

The compute rethink: Scaling AI where data lives, at the edge Read More »