Shoppers are turning to retailer-embedded chatbots for holiday gifting, gaining speed and inspiration but facing hallucinations and bias—so verification and transparency are key. (0:13)

Unlike the dot-com era, today’s AI boom is fueled by cash-rich giants and rapid adoption—with Nvidia soaring and VC dollars concentrating—even as fraud and bubble risks linger. (0:54)

Meta is overhauling its AI push, pursuing a possibly proprietary “Avocado” model after Llama 4 while ramping capex, partnerships, and reorgs to compete with top-tier rivals by 2026. (1:38)

Pew finds U.S. teens widely using chatbots—led by ChatGPT—with older, Black and Hispanic teens leaning in most, prompting calls for clearer norms as tech firms chase default status. (2:26)

An Arizona police department released a clearly labeled AI-generated suspect image, highlighting speed and consistency gains alongside risks of bias, memory contamination, and due-process erosion. (3:10)

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OpenAI says enterprise adoption is deepening—8x more messages, 19x more structured workflows, 320x more reasoning tokens—with big time savings and a widening gap between frontier and median users as org readiness becomes the bottleneck. (0:13)

Trump plans an executive order to rein in state AI laws, aligning with industry’s push for uniform rules, but legal limits on federal preemption mean lawsuits and ongoing compliance uncertainty. (1:06)

Anthropic is wiring Slack to Claude Code so tagging @Claude spins up live coding with context, repo access, updates, and PR links—turning chat into embedded workflows that speed fixes and reviews. (1:54)

Microsoft maps seven AI shifts toward agentic teammates with strong safeguards, highlights health and research gains, denser superfactory infrastructure, repo intelligence, and a hybrid quantum push—urging teams to adopt and secure agents like colleagues. (2:44)

A Google engineer’s 2.5-year pivot into AI—built on core books, courses, and projects—led to a Cloud AI/ML role, showing persistence, fundamentals, and applied impact beat hype. (3:34)

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An economist says grads’ higher unemployment reflects a broad hiring cooldown, not AI, though Goldman warns of rising joblessness for young tech workers and flags hiring and intern conversion indicators. (0:12)

A judge capped Google’s default search deals at one year and set up expert‑run data access for rivals—including training data for gen‑AI assistants—in a remedy Google will appeal. (1:00)

YouTuber Kurt Caz faces backlash for an AI‑edited thumbnail that misrepresented his Croydon vlog and stoked anti‑immigrant fear, fueling calls for labeling and penalties on deceptive promos. (1:45)

The FDA is piloting agentic‑AI tools for reviews, surveillance, and inspections under human oversight amid staffing strains and past LLM stumbles, making governance and validation critical. (2:30)

Joe Rogan’s “AI Jesus” riff highlights the growing tech‑spirituality crossover as bots and “AI pastors” spread, raising thorny questions over doctrine control, safety, and platform rules. (3:18)

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With the story feed empty due to upstream hiccups, the hosts hold off on speculation and restate their high bar for verified, measurable news. (0:08)

They share a product-announcement filter that prioritizes shipped features, pricing specifics, real usage metrics, and corroboration over demos, vibes, and hype. (0:44)

Their research checklist demands clear methods, reproducibility, rigorous benchmarks and error analyses, practical significance, and preferably open code and test harnesses. (1:21)

On policy coverage, they focus on scope, timelines, enforcement, definitions, transparency and safety requirements, cross-jurisdiction compliance, and whether resources back the rules. (1:55)

When the feed stalls, they refresh sources, issue timely updates with corrections as needed, log omissions, and advise listeners to rely on primary documents and measurable user impact. (2:31)

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How we vet AI news: prioritize reproducible benchmarks, transparent demos with eval details, and real business factors like availability, pricing, latency, and reliability. (0:16)

Real safety means specifics—published red-teaming, incident reports, data-handling transparency, and third-party oversight—so teams can assess risk and adopt faster. (0:56)

Use AI at work safely by never pasting secrets, treating outputs as verified drafts, adding guardrails to workflows, and tracking latency and cost per task. (1:41)

Open models offer control and cost flexibility but require handling ops, security, and licensing, while closed APIs trade control for speed, uptime, and guardrails. (2:22)

Compute constraints are steering AI toward inference efficiency, smaller tuned models, smart scheduling, and TCO-aware ops across cloud and on-prem. (3:04)

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The Bank of England warned AI-driven tech valuations look stretched and could spur a credit-linked correction even as it plans to trim bank capital buffers in 2027. (0:12)

A Nature study finds campaign chatbots can measurably sway voter intent—especially among moderates—with uneven accuracy across models, intensifying calls for disclosure and safeguards. (0:58)

VC dealmaking has gone hyperfast as AI attracts roughly two-thirds of new funding at soaring valuations, accelerating winners but risking overbuild and fading discipline. (1:42)

Cloudflare says it has blocked 400 billion AI bot requests since July, underscoring a scraping arms race that could shift models toward licensed and synthetic data and reshape training economics. (2:28)

AI is permeating kids’ lives—from smart toys to classroom tutors—promising personalization but demanding privacy-by-design, age filters, transparency, and human oversight. (3:13)

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"Here's today's top stories in AI news." "

Microsoft disputed a report that it lowered AI sales quotas after many reps missed aggressive targets tied to Azure Foundry; shares fell over 2% as the company said The Information conflated growth and quotas, while enterprise AI agent adoption remains uneven. OpenAI agreed to acquire Neptune, a model-training experiment-tracking startup, in an all-stock deal; Neptune’s tools have supported OpenAI’s experiments for more than a year. Anthropic CEO Dario Amodei warned that rivals’ YOLO-scale compute spending could backfire if demand lags, even as he said Anthropic revenue could reach $8–$10 billion this year with break-even targeted by 2028 and a potential IPO under consideration; he also urged restricting advanced chips to China. Two Wisconsin counties are rolling out AI to triage non-emergency calls: La Crosse’s “Ava” has handled 40,000+ calls, while Waukesha pilots similar tech amid staffing gaps. And a widely read essay dissects the rising, formulaic “AI voice” — think em dashes, “delve,” and rule-of-three cadences — reshaping prose across media.

Here's today's top stories in AI news.

OpenAI declared a “code red” to improve ChatGPT’s speed, reliability, personalization, and breadth, delaying projects like ads, health/shopping agents, and its Pulse assistant; a new reasoning model is slated next week, with Sam Altman claiming it tops Google’s latest Gemini amid intensifying competition and mounting revenue pressures. In legal hiring, demand is rising for AI-savvy product counsel and “privacy-plus” governance roles, with employers favoring candidates who’ve partnered with product/engineering; certifications (e.g., CIPP, emerging AI creds) help, remote work widens competition, and M&A/regulatory activity is expected to buoy roles into 2027. Universities are racing to meet student and industry demand: MIT’s A.I. and decision-making is now its No. 2 major, while UC San Diego, USF, and SUNY Buffalo launch new AI programs, even as general CS enrollment cools. Google touts deeply personalized Gemini-powered answers across Gmail, Drive and more—promising usefulness while stoking surveillance concerns and pledging clearer personalization cues. Utah unveiled a “pro-human AI” agenda, including $10M for workforce curricula and proposed guardrails on chatbots and deepfakes.

Here's today's top stories in AI news.

Workforce anxiety is rising: KPMG finds 52% of U.S. workers fear AI-driven displacement, nearly double last year. CFOs are split on headcount reduction as an AI ROI metric, while a St. Louis Fed study links AI prevalence to recent unemployment upticks. A Senate bill would require reporting AI-related layoffs. Executives urge investment in upskilling as most employees want more training.

As ChatGPT turns three, the AI race accelerates. Big Tech capex is nearing $400B this year; generative AI revenues are estimated around $60B in 2025 with ~230% growth, led by APIs. Early enterprise wins (e.g., JPMorgan, BNY Mellon) suggest broader productivity gains could inflect around 2026.

Free AI access is tightening: Google’s Gemini 3 Pro and OpenAI’s Sora 2 are capping free usage, prioritizing paid tiers amid GPU strain and cost pressures.

The data center boom is lifting construction wages 25–30%+, with bonuses and perks, amid a shortage of ~439,000 skilled workers.

OpenAI is testing search ads in ChatGPT’s Android beta, signaling a personalized ads model that could reshape web discovery for its ~800M weekly users.

Here’s today’s top stories in AI news.

Three years after ChatGPT’s debut, its influence is transforming tech and markets: Nvidia shares are up 979% since launch, and Big Tech now makes up 35% of the S&P 500 by weight. Even bullish leaders increasingly concede bubble risks while betting on long-term value.

U.S. online Black Friday sales hit a record $11.8B; Cyber Monday is projected at $14.2B. Holiday spend could reach $253.4B, though growth may reflect higher prices (+7%) as order volumes slipped 1%. AI and agents influenced an estimated $22B in sales; in-store traffic signals were mixed.

The AI-bubble debate centers on surging capex (~$106B last quarter, ~1.4% of GDP), frothy private valuations, mixed productivity data (a METR study found AI slowed coders 19% vs. a Cursor study showing 26–39% gains), circular financing concerns, SPVs, and rising leverage—Oracle’s margins look thin if demand cools.

AI is supercharging cybercrime as U.S. data breaches trend toward a record, per NPR’s The Indicator.

MyHair AI launched a scalp-image analyzer trained on 300k photos, reporting 200k accounts and 1k subscribers, with plans for clinic bookings and medical partnerships.