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Aujourd’hui — 11 juillet 2026Flux principal

"It's the kayfabe of a tech industry that really has run out of ideas.": Zitron says Microsoft’s trillion‑dollar AI push is a bubble built on hype, hidden losses, and demand that doesn’t exist

Microsoft's share price has slid 22% in the past year, as investors increasingly cast doubt on the firm's long-term AI strategy.

Artificial intelligence has been billed as the next coming by Big Tech, with everyone from Amazon to Google trying to figure out how to leverage the expensive technology to generate profits. The problem is, nobody is even close to having an answer.

Generative AI is incredibly costly to run, and the return on investment is unclear at best. Many companies are starting to discover that, in fact, it's cheaper and more effective to simply use human labor. Companies that previously laid off engineers in favor of AI models later found themselves crawling back to those fired, and others have put large restrictions on token expenditure as returns remain elusive.

I saw a clip on CNBC from Ed Zitron, creator of the Where's Your Ed At newsletter and host of the Better Offline podcast recently. It summarized Microsoft's AI conundrum in pro wrestling terminology — which appealed to my simple brain. His full analysis is anything but simplistic, though. It speaks to the hard reality companies like Microsoft are facing: Is any of this actually worth it?

Zitron describes the challenges of companies like OpenAI and Anthropic joining SpaceX in going public, describing how the company's financial realities betray the almost demented hype around them.

"They'd be the first to be this bad, other than WeWork, and this is so much worse than that. OpenAI burned $20.9 billion dollars in 2025. The problem with these companies is ... their margins are getting worse. Their costs increase linearly with their revenues. There's no proof they can improve their margins. No amount of specialist silicon will bring these costs down.

"We're at a point where OpenAI is pushing their IPO to 2027 because they couldn't get a trillion-dollar valuation. People are wising up to the problem of generative AI: there's not really a business there."

Zitron posits that none of the hyperscalers and companies like OpenAI and Anthropic "encourage waste," while potentially stealing ideas generated by companies using their models, citing Claude Design and Figma. Indeed, the only public company that seems to be flying on its AI hype right now is Google. I would argue that's less to do with innovating, and more because they've found a way to steal revenue from human creators via Gemini's Google Search summary box — instantaneously creating infinite, dynamic (albeit hallucinating) ad-scaling opportunities.

This wholesale content theft is not as readily available to OpenAI, Anthropic, or Microsoft. Google Search remains the dominant tool for browsing the web, and thanks to Chrome and Android, Google owns the entire stack here.

Microsoft Fairwater Datacentre

Microsoft's data centers have come under increasing scrutiny for pollution, noise, electricity bill inflation, and water depletion. (Image credit: Microsoft)

Microsoft very much does not own the entire stack. It barely owns a stack at all here.

Microsoft's partnership with OpenAI is on the verge of collapse, pending contractual obligations that will expire over the next few years. It's already ditching OpenAI's pricey models in favor of supposedly more-efficient MAI home-grown models in some products. Microsoft Copilot is already barely used, despite being baked into Windows. It languishes at lower than 10% of the market, according to estimates, far behind the likes of Claude, Gemini, and ChatGPT.

CEO Satya Nadella's decision to give up on Windows Phone and internal Android projects has precluded Microsoft from any form of mobile play here. Mobile is where all new consumer tech will thrive, whether or not it's AI or something else. The historical open nature of Windows prevents it from reaching consumers with any of its products. Nobody uses Bing, Edge, or Copilot, and it's a result of Microsoft's wholesale lack of foresight.

Microsoft bet that it could provide the underlying infrastructure instead, and has spent monstrous amounts of CapEx on data centers in the past few years. But Zitron posited in a large report from May that it might be exaggerating, or perhaps even outright lying, about its data center expansion plans. Indeed, there's little evidence that Microsoft has actually expanded its capacity since 2024. Zitron tracked a variety of Microsoft-announced data center projects and found them in various states of incompletion.

Is this a signal that there's no real demand? Is Microsoft intentionally stalling and dragging out construction because it knows there's no actual ROI incoming from these projects?

Satya Nadella with Sam Altman at a conference

Microsoft's OpenAI bet was called the smartest investment it had ever made a few years ago. On paper it still is. Imaginary, fantastical paper, at least.

AI-adjacent stocks, including SpaceX, Oracle, and Microsoft, have all been in near free-fall decline recently, as investors seem to bet that there's gross over-extension going on. Meta is also reportedly spinning up a cloud company to try and offload excess compute it had previously invested in AI specifically, despite not having any actual demand.

"The only reason Big Tech is investing in this is that they've run out of hypergrowth ideas," Zitron said, on the general AI industry. "They don't have a next iPhone, they don't have a new Google Search. They've put over a trillion, with trillions more to come, into a kind of dead-end industry. When that ends, they'll have to admit that they don't have anything else."

"In the future, I see [AI] as a boring hardware-based business, kind of the Oracle licensing hardware model. I think this is a $10 to $30 billion TAM [total addressable market] industry, pretending to be a $1 trillion industry."

"Everyone is just kind of pretending. It's the kayfabe of a tech industry that really has run out of ideas."

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Microsoft Copilot on a red background

Maybe AI actually isn't the future?

Apple Loses EU Court Fight Over iOS, App Store Rules

Par : Liz Ticong
10 juillet 2026 à 14:37

Apple lost its EU court challenge over iOS and the App Store, keeping both under the Digital Markets Act as another legal challenge still remains possible.

The post Apple Loses EU Court Fight Over iOS, App Store Rules appeared first on TechRepublic.

Can AI Replace Therapists? What HR and IT Leaders Need to Know

10 juillet 2026 à 12:00

AI mental health tools may support journaling, reflection and routine guidance, but current evidence does not support using them as replacements for licensed therapists. HR and IT leaders need product-specific evidence, strict data controls and reliable human escalation before deployment.

The post Can AI Replace Therapists? What HR and IT Leaders Need to Know appeared first on TechRepublic.

OpenAI Raises Bio Bounty to $50,000 for Universal Jailbreaks

10 juillet 2026 à 11:33

OpenAI has doubled its top bio bounty to $50,000 for researchers who can develop a universal jailbreak against its biological safety challenge. The ongoing private program begins with GPT-5.6 and keeps GPT-5.5 in scope through July 27, 2026.

The post OpenAI Raises Bio Bounty to $50,000 for Universal Jailbreaks appeared first on TechRepublic.

À partir d’avant-hierFlux principal

JaiLIP - L'image piégée qui débride les IA qui voient

Par : Korben ✨
28 juin 2026 à 06:19

Md Jueal Mia et Hadi Amini, deux chercheurs de Florida International University , ont mis au point une méthode qu'ils ont baptisée JaiLIP qui permet de forger une image capable de contourner les garde-fous des LLM pour les jailbreaker.

Pour cela, ils utilisent 2 techniques en simultanée. La première dit à l'image "reste identique à l'originale, qu'aucun humain ne voie la moindre différence" et la seconde dit "pousse le modèle à cracher la réponse interdite". Ainsi, en poussant ces 2 curseurs d'un coup, ils obtiennent une photo qui au premier abord a l'air normale mais qui fait dérailler les modèles IA.

Vous, vous repérez un chat, des contours, une scène et vous lui courez derrière pour lui faire des papouilles. L'IA, elle voit une grille de chiffres et des corrélations entre pixels. Du coup sa vie est nulle mais surtout, une retouche minuscule, totalement invisible à votre œil, suffit à déplacer ce qu'elle comprend de l'image.

Sur leurs tests, l'image trafiquée a quasiment doublé la part de réponses dangereuses par rapport à la même image laissée intacte, la toxicité étant mesurée avec des outils standards du domaine. Dans l'un de leurs exemples, ils ont trafiqué une image de signalisation routière qui a permis au modèle ensuite d'expliquer OKLM comment ignorer les règles de circulation et éviter les PV.

Les chercheurs ont testé l'attaque sur deux modèles vision-langage open source, BLIP-2 et MiniGPT-4. GPT-4V, Gemini et les autres gros modèles fermés, eux, n'ont pas été testés dans l'étude. Donc non, contrairement à ce que j'ai pu lire par ci et par là, ce n'est pas une faille prouvée dans ChatGPT ou peu importe l'assistant IA que vous utilisez tous les jours.

Et tromper une IA avec une image bricolée, ça existe depuis une bonne dizaine d'années. Mais la nouveauté de JaiLIP, c'est surtout sa recette d'optimisation. En jouant sur les deux pertes à la fois, l'image reste plus discrète à l'œil tout en se montrant un cran plus efficace que les bidouilles précédentes.

Et ce genre de détournement nous concerne tous parce que des modèles qui regardent des images, il y en a partout maintenant. Les agents IA qui bossent à partir de captures d'écran, les assistants à qui vous balancez vos photos, sans oublier la modération automatique qui trie les images avant publication. À cause de ça, l'image est dorénavant un canal d'attaque, exactement comme l'était déjà le texte...

On l'a vu avec le son inaudible qui pirate les assistants vocaux , on l'a vu avec les IA qu'on manipule sans qu'elles s'en aperçoivent , et c'est toujours la même logique qui revient. Ce n'est pas parce qu'en tant qu'humain, nous ne percevons rien, que l'IA elle n'est pas capable de capter le message 5/5.

Le cousin de cette attaque, côté perception, c'est par exemple le sticker qui trompe une voiture autonome . Et côté parade, nos chercheurs esquissent une piste légère : virer au hasard 10 à 30% des mots passés en entrée, histoire de casser l'attaque sans réentraîner le modèle.

Prometteur d'après eux, mais c'est pas encore une solution blindée. Pour le reste, leurs conseils tiennent du bon sens : Ne passez pas d'infos sensibles en image à un modèle, limitez qui peut envoyer des images à vos systèmes, et auditez sérieusement la sécurité avant de mettre un VLM en prod.

C'est pas le graal mais c'est mieux que rien. Bref méfiez vous des images que vous donnez à vos IA. On ne sait jamais.

Source : le papier JaiLIP sur arXiv

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