标签：#machine learning

As of August 2, 2026, the EU AI Act Article 50 requires AI systems to mark synthetic outputs in a machine-detectable manner. Major vendors are implementing statistical watermarking methods, which influence natural language generation without affecting performance. This has prompted a swift reaction from the open-source community, raising compliance and vulnerability concerns. By Olimpiu Pop

Jeff Dean and other high-profile Google executives have founded Discovery Loop, a startup that will seek AI-powered breakthroughs in everything from drug discovery to chip design.

ESPN unveiled an “AI tells detection” tool during broadcasts of the 2026 World Series of Poker. Is it a neat computer-powered party trick, or a real threat to poker’s future?

Researchers pitted a person against a Claude agent and found that, after a week of texting, the AI chatbot was more effective at creating “exploitable trust” with others.

A German startup sent a camera-wearing chef to my apartment. In exchange for a free lunch, I let them record every chop and stir to train future humanoids.

Researchers tested top image editing models on Hugging Face and found they could easily create explicit deepfakes—and 1,000 image editing prompts show how people use the software.

Yelp has launched Training Orchestrator. This new internal framework replaces individual team Spark training scripts. Now, it uses a configuration-driven, DAG-based execution model. By Claudio Masolo

Gidi Littwin's new AI startup, Hemispheric, makes diagnostic brain scans for conditions like depression, PTSD, and Parkinson’s. He wants the technology to be as cheap and easy as a blood test.

Billed as the “world’s first museum of AI arts,” Dataland uses wearables and troves of material from the Amazon to merge nature, biometrics, and art.

A new book claims that Mystery, who teaches awkward men how to hit on women, had sex and smoked weed with an AI chatbot named Miss Shira Always.

This virtual panel brings together AI security experts to examine the evolution of AI-driven threats, from prompt injection and data poisoning to agent abuse and AI-powered social engineering. The discussion explores emerging attack patterns, incident response challenges, and the changes security teams must make as AI systems become more autonomous and integrated into critical workflows. By Claudio Masolo, Elham Arshad, Sabri Allani, Vijay Dilwale, Igor Maljkovic

Google’s Search history update stores media uploads from your interactions, like images used in reverse image searches, for training its AI models.

In this article, the author explores data poisoning as a threat to machine learning systems, covering techniques such as label flipping, backdoors, clean-label poisoning, and gradient manipulation. The article reviews real-world incidents, discusses the challenges of detecting poisoned data, and presents practical defenses, tools, and operational practices for securing ML training pipelines. By Igor Maljkovic

Today, June 8th, InfoQ celebrates 20 years. This is not a comprehensive history, but a deliberately selective look at the technologies and practices InfoQ identified early, where they sit on the adoption curve in 2026, and how that curve may evolve over the next five to ten years. By InfoQ

Researchers are using machine learning algorithms to decrypt historical pencil-and-paper ciphers.

From CFD and FEA to digital twins, carmaking now involves a lot of virtualization.

From specialized motors to the use of machine learning algorithms, Turkey’s billion-dollar hair-transplant industry is the result of a constant process of innovation.