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AI Product manager
A seasoned AI professional driving business growth through strategic AI adoption, with a focus on developing and managing AI products, infrastructure, and governance frameworks that balance innovation with regulatory compliance. They prioritize staying updated on the latest AI models, capabilities, and MLOps advancements.
Ai strategy (20%)Models & Capabilities (20%)Ai Infrastructure & MLOps (20%)Generative AI (20%)User Experience Design (20%)
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AI Strategy, Generative AI, Model Open‑Source, User‑Centric Governance, Infrastructure Energy…
Mardi 16 décembre 2025 à 07:50
AI Strategy — Navigating Investment Hype and Organizational Alignment
The AI “bubble” debate sharpens strategic caution
MIT Technology Review notes that a recent MIT study found 95 % of firms investing in generative AI reporting zero return, prompting OpenAI CEO Sam Altman to label the market “over‑excited.” Executives from Meta, Google and OpenAI echo concerns that massive data‑center build‑outs—some projected at 250 GW—may outpace realistic revenue, warning of a potential bust that could strain over‑leveraged startups.
MIT Technology Review
Employees see AI tools, but firms hide the roadmap
A Gallup survey reported by ZDNet shows 45 % of U.S. workers now use AI at work, yet 23 % are unsure whether their employers have adopted AI at scale. The study highlights a communication gap that hampers coherent AI governance and can lead to misaligned expectations between leadership and staff.
Zdnet
Generative AI — Partnerships, Content Risks, and Market Dynamics
Disney’s one‑year exclusive with OpenAI fuels content creation bets
TechCrunch reveals Disney has struck an exclusive, year‑long agreement with OpenAI to embed generative AI into its media pipelines, after which the deal opens to competitors. Analysts view the pact as a strategic hedge, positioning Disney to leverage cutting‑edge language models while testing monetisation pathways before broader market rollout.
TechCrunch
AI‑generated recipes threaten food‑blogger livelihoods
The Guardian reports Google’s AI‑Mode now auto‑creates recipe pages, often blending instructions from multiple sources and even mis‑attributing satirical content as genuine. This “extinction event” for culinary creators underscores the unintended commercial fallout of generative AI on niche content ecosystems.
The Guardian
Models & Capabilities — Open‑Source Advances and AGI Forecasts
Prediction markets reveal divergent AGI timelines
The Information highlights that betting platforms such as Polymarket and Kalshi assign OpenAI an 11‑15 % chance of announcing AGI next year, while Manifold markets split expectations around a 2036 horizon. These odds, driven by insider sentiment, illustrate the speculative nature of AGI timelines among informed participants.
The Information
Nvidia’s Nemotron 3 family pushes open‑model frontier
Computer World details Nvidia’s release of the Nemotron 3 series—Nano, Super and Ultra—featuring a hybrid latent mixture‑of‑experts architecture that boosts token throughput four‑fold while slashing inference costs. By open‑sourcing weights, training data and RL libraries, Nvidia aims to become the infrastructure layer for enterprises building bespoke AI agents, challenging closed‑API rivals.
Computer World
User Experience Design — Governance and Agentic Interfaces
GNOME bans AI‑generated extensions to preserve code quality
The Verge reports the GNOME Shell Extensions store now rejects submissions that appear primarily AI‑written, citing risks of unnecessary code, inconsistent style and “imaginary API” usage. This policy reflects a broader push to ensure maintainable, human‑vetted extensions within open‑source ecosystems.
The Verge
IBM’s CUGA agent targets half‑task automation in enterprises
The Register covers IBM’s open‑source CUGA framework, which promises to complete roughly 62 % of complex workflow steps autonomously. While still experimental, CUGA signals a shift toward semi‑automated agents that can augment human operators without full reliance on proprietary services.
The Register
AI Infrastructure & MLOps — Energy Constraints and Data‑Pipeline Growth
“Bragawatt” data‑center era strains power grids, sparks innovation
The Information’s “AI Infrastructure” newsletter warns that projected AI compute demand (up to 100 + GW in the U.S. by 2030) far exceeds current grid capacity, prompting firms like OpenAI and Microsoft to explore behind‑the‑meter power and efficiency breakthroughs. This pressure is catalysing advances in grid‑enhancing technologies and off‑grid renewable installations.
The Information
The data‑labeling boom reshapes AI training pipelines
The Verge’s deep dive into Mercor, Scale AI, Surge and other “picks‑and‑shovels” firms shows a surge of $10 billion‑plus annual spend on high‑quality human‑annotated data. As large‑scale models become compute‑constrained, bespoke datasets and granular rubrics are emerging as the new bottleneck for AI progress, redefining the MLOps landscape.
The Verge
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