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A Google Cloud survey found that 90% of developers are already integrating AI into their daily work, and on Steam, 7,818 titles disclosed AI use in 2025 alone, a 681% increase over the previous year. AI in video game development is not a side experiment.
In 2024, researchers from the University of Illinois found that GPT-4, when provided with a common vulnerabilities and exposures (CVE) description, could autonomously exploit 87% of a curated 15-vulnerability one-day dataset. Without the description, it could only exploit 7%.
As enterprise AI agents move into production, organizations are confronting a growing reliability problem. Many teams are discovering that LLM performance alone does not determine whether agents succeed in production.
Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits. MeMo, a framework from researchers at multiple universities, encodes new knowledge into a dedicated smaller memory model that operates separately from the main LLM.
Anthropic today released Claude Opus 4.8, an upgrade to its flagship model that ships at the same price as its predecessor, alongside a dramatically cheaper "fast mode" tier and a new feature that lets the model spawn hundreds of parallel subagents for codebase-scale work.
DeepSeek’s announcement over the weekend that it has made its 75% price cut permanent on its flagship V4 Pro model is a disruptive assault on the capital-heavy business models of Silicon Valley’s frontier labs. The reduction on DeepSeek V4 Pro directly undercuts comparable Western models used as workhorses for enterprise production.
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Climate tech companies are going public.
The data processing agreement (DPA) — the bedrock contract companies use to evaluate how vendors handle personal data — can no longer be trusted at face value. That is the central, and arguably most alarming, conclusion of DataGrail's Privacy and AI Trends Report 2026, released today.
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Stay on top of what’s going on in AI this summer Here at MIT Technology Review, we understand exactly how relentless the pace of news from the world of artificial intelligence….
For months, the leading AI coding benchmarks have told enterprise buyers a comforting but misleading story: the top models are all roughly the same. OpenAI's GPT-5 family, Anthropic's Claude Opus, and Google's Gemini Pro have clustered within a narrow band on Scale AI's SWE-Bench Pro leaderboard, making it nearly impossible for engineering leaders to determine which agent will actually perform best inside their codebases.
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. A reality check on the AI jobs hysteria Despite the growing hysteria over AI’s threat to white-collar jobs, there’s still scant evidence that the technology has had a large-scale impact on….
Over the past two decades, technical debt meant outdated architecture, messy code, and poorly maintained documentation. That definition is no longer sufficient in the AI era, where failure modes are more subtle and often non-linear.
There is a category of production incident that engineering teams are not tracking yet — because it doesn't fit any existing postmortem template. The agent initiated an action.
When agentic workflows fail, developers often assume the problem lies in the underlying model’s reasoning abilities. In reality, the limited information provided by the retrieval interface is often the primary limiting factor.
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Anthropic’s Code with Claude showed off coding’s future—whether you like it or not At Anthropic’s developer event in London this week, Code with Claude, attendees were asked if they’d shipped code….
Every major economy is staring at the same problem right now. Artificial intelligence is consuming electricity at a pace that grids were never designed to handle.
The AI industry has fully entered the "agent era," a paradigm where AI models do far more than generate text — they now actively plan, execute, and course-correct complex tasks over days rather than seconds. Thus, it's perhaps unsurprising to see Chinese e-commerce giant Alibaba's famed Qwen Team of AI researchers release a model capable of performing autonomous agentic AI work over multiple days: that model has arrived in the form of Qwen3.
The vibes were strong at Code with Claude, Anthropic’s two-day event for software developers in London that kicked off on May 19, the same day as Google’s I/O in Palo Alto. (A coincidence, not a flex, Anthropic staffers assured me.
At Google I/O, the company unveiled Managed Agents in its Gemini API — a service that promises to collapse weeks of agent deployment work into a single API call. It's also a sign that Google believes its ecosystem, including the newly launched Antigravity CLI, is ready to own the execution layer end-to-end.
Google unveiled Gemini 3.5 Flash at its annual I/O developer conference on Tuesday, a new artificial intelligence model that the company says shatters what had become a seemingly iron law of the AI industry: that the smartest models must also be the slowest and most expensive to run.