B. Riley warns AI network flattening could crush traditional transceiver demand

Wedbush managing director and senior equity research analyst Dan Ives believes one lagging group of stocks will surprise investors in the next six months. In an interview with Bloomberg Television, Ives says that while many investors have taken their eyes off the Magnificent 7 due to their massive AI spending, he believes that the hyperscalers […] The post Wedbush’s Dan Ives Predicts One Stock Group Will ‘Significantly Outperform’ in Second Half of 2026 appeared first on The Daily Hodl.

FCA’s review into how tech will reshape financial services warns about amplified risks of cyber-crime and fraud Business live – latest updates Ministers have been urged to toughen the City regulator’s powers to protect consumers against the potential risks of AI, according to a landmark review. The Financial Conduct Authority’s (FCA) Mills review, which looked at how AI will reshape financial services from 2030 onward, found that companies are already starting to shift from human-led activities towards AI-enabled services for everyday consumers. Continue reading...

Researchers say small changes in drafting could spread rapidly and create long-term shifts in public opinion AI tools are twisting online messages on sensitive political topics about everything from abortion to climate change in ways that could snowball to reshape long-term public opinion, experts have said. As tech companies push AI tools as convenient ways to redraft and summarise the massive influx of daily messages, many inject their own political biases – some leaning distinctly rightwing, others more liberal, according to a study from Oxford and Potsdam universities. Continue reading...

As intelligent systems move into production environments and begin taking actions, organizations quickly discover that accountability becomes much harder. Unlike traditional enterprise software, these tools can produce unpredictable outcomes as they interact dynamically with data, APIs, and business workflows. “When something goes wrong with AI, it is generally assigned to whoever was closest to the pain point,” says David DuChene, manager of data and AI pre-sales at SHI International, which works with enterprises on AI deployments and governance. As these systems shift from advisor to actor within workflows, accountability becomes harder to enforce through policies alone. IT leaders must build it directly into the fabric of their operations through clear ownership, continuous observability, defined escalation paths, and infrastructure designed to make responsibility visible when things go wrong. Here are six ways to make AI accountability enforceable in production. 1. Assign direct ow

SK Hynix's Nasdaq listing could reshape AI infrastructure, amplifying its market influence and potentially impacting global tech ecosystems. The post SK Hynix estimates net proceeds of $28B in massive Nasdaq ADR offering appeared first on Crypto Briefing.

Coinbase came under fire after an artificial intelligence (AI)-generated alert told users Norway had beaten Brazil 3-2 in a World Cup knockout match that had not yet been played. A Major Goof up Coinbase declared that Norway had defeated Brazil 3-2 with striker Erling Haaland scoring twice. The problem was that the match, scheduled for […]

What is Medical Data De-Identification? Medical data de-identification involves removing or masking personal details of patients from their health records, such as names, dates, location details, ID numbers, and faces in photos or biometrics. This breaks the link between the medical data and the individual, protecting privacy while allowing AI developers and researchers to use… Continue reading De-Identifying Clinical Data for AI: A Technical and Regulatory Guide The post De-Identifying Clinical Data for AI: A Technical and Regulatory Guide appeared first on Cogitotech.

What is Medical Data De-Identification? Medical data de-identification involves removing or masking personal details of patients from their health records, such as names, dates, location details, ID numbers, and faces in photos or biometrics. This breaks the link between the medical data and the individual, protecting privacy while allowing AI developers and researchers to use… Continue reading De-Identifying Clinical Data for AI: A Technical and Regulatory Guide The post De-Identifying Clinical Data for AI: A Technical and Regulatory Guide appeared first on Cogitotech.