Course correction: Google to link more sources in AI Overviews

Hovering over links in AI answers will soon show preview pop-ups.

Credit: Google

Hovering over links in AI answers will soon show preview pop-ups. Credit: Google

While most of the newly announced AI features will roll out soon, Google is still seeking partners to support one of them. Google is seeking publishers that are interested in testing a new form of subscription integration. The company says your favorite websites should appear more prominently in AI search, so it’s trying to make that happen in AI Overviews and AI Mode. This feature will use an API to link a reader’s subscription on a website with their Google account. Google says that early testing showed users were much more likely to click through when their subscribed websites appeared as links in AI answers. Interested publishers are invited to fill out a form to get more information.

Live by the web, die by the web

Google does not accept the conventional wisdom that AI search is reducing website traffic. However, various analyses have suggested that the chatbot is stopping users from leaving Google’s platform. That might be fine for Google right now, but Gemini only works as a search product if it has a vast sea of online data to summarize. As websites increasingly feel the squeeze of lower traffic (and advertising revenue), there may be less of that content available.

Google also has to be aware that the growing AI backlash goes beyond existential threats to the web—it’s also an immediate legal liability. Publishers, artists, and authors have filed lawsuits against the company alleging that Gemini is illegally using their content. Penske Media has alleged that searches with AI Overviews can reduce clicks by as much as 90 percent. Meanwhile, Google is under increased scrutiny in Europe now that the Digital Markets Act is in full effect, which could force it to create an AI Overviews opt-out for websites.

These changes may represent a bit of a course correction for Google after AI tools created too many zero-click searches. It’s unclear if just adding more external links to AI answers will get the job done, though.

https://arstechnica.com/google/2026/05/google-will-put-more-links-to-websites-in-ai-overviews/




Chrome’s 4GB AI model isn’t new, but you’re not wrong for being confused

A curious omission

Google users were more willing to excuse AI in 2024, but the backlash is real in 2026. People are increasingly looking to avoid AI features, which makes this 4GB stealth download all the more questionable. Google’s obsession with AI has led to numerous stumbles, even when the company has ostensibly good intentions, because we are all (rightly!) hyper-focused on how this technology is impacting our lives.

Some of those “good intentions” seem to have made the Chrome situation worse. As users sought ways to remove this AI model, many looked for the settings toggle. This happened to coincide with the wide release of Chrome 148, and the label for this toggle included a pretty suspicious change versus v147.

Chrome AI toggles

Google claims this change was made to be clear about how Chrome’s APIs work.

Credit: Ryan Whitwam

Google claims this change was made to be clear about how Chrome’s APIs work. Credit: Ryan Whitwam

Google removed the stipulation that its on-device AI model would not send data to Google’s servers. This is alarming, as one of the primary benefits of local AI is its greater privacy. We reached out to Google to ask if this wording is due to a change in Chrome’s on-device AI.

“This doesn’t reflect a change to how we handle on-device AI for Chrome,” a Google spokesperson said. “The data that is passed to the model is processed solely on device.”

According to Google, the team decided to make this change earlier in 2026 to ensure it was being crystal clear about how AI works on the web. Chrome’s local AI has an API that a site might use, for example, to do summarization or edit your writing. In these instances, the website would naturally see the input and output. If it’s a Google website, that data ends up on Google’s servers. If it’s a non-Google site, Google doesn’t see any of that data.

That explanation may or may not be satisfying as the backlash against AI grows. Regardless, using the web is never completely private. If you’re uncertain about using AI tools on a site, you should always try to parse its privacy policy, which will tell you how your data (AI-generated or not) will be used. As long as Google is deploying AI as an opt-out service, you’ll have to be extra vigilant.

As the saying goes, it’s easier to ask for forgiveness than permission, but Google ought to be asking for permission a little more often.

https://arstechnica.com/google/2026/05/no-google-hasnt-changed-chromes-local-ai-features-its-just-as-confusing-as-ever/




AI, Anthropic si garantisce l’accesso al supercomputer di SpaceX e ai chip avanzati di Google

L’accordo di Anthropic con SpaceX e xAI per l’utilizzo del supercomputer Colussus 1 e dei futuri data center orbitali

Anthropic, la società che sviluppa i modelli di intelligenza artificiale Claude, ha siglato due accordi strategici che mostrano la vera dimensione della corsa globale all’AI: non conta più soltanto la qualità degli algoritmi, ma soprattutto la disponibilità di infrastrutture di calcolo.

Il primo accordo riguarda SpaceXAI e xAI, che metteranno a disposizione di Anthropic il supercomputer Colossus 1, descritto come uno dei sistemi AI più grandi e rapidi mai costruiti. Il cluster dispone di oltre 220.000 GPU NVIDIA, incluse H100, H200 e future GB200, ed è progettato per addestramento, inferenza e simulazioni AI su scala estrema. Anthropic utilizzerà questa capacità aggiuntiva per aumentare le prestazioni dei servizi Claude Pro e Claude Max.

L’intesa prevede inizialmente circa 300 megawatt di capacità computazionale supplementare, una potenza paragonabile a quella assorbita da grandi data center hyperscale. Il dato rende evidente quanto il fabbisogno energetico dell’intelligenza artificiale stia crescendo rapidamente: la potenza necessaria per addestrare e far funzionare i modelli di nuova generazione sta mettendo sotto pressione reti elettriche, sistemi di raffreddamento e disponibilità di hardware.

L’aspetto più ambizioso dell’accordo riguarda però il lungo periodo. Anthropic ha infatti manifestato interesse a collaborare con SpaceX per sviluppare infrastrutture AI orbitali da più gigawatt. L’idea nasce dalla convinzione che, in futuro, i limiti terrestri legati a energia, spazio fisico e raffreddamento potrebbero non essere sufficienti per sostenere la crescita dell’intelligenza artificiale. SpaceX ritiene di essere l’unica azienda con la frequenza di lanci e l’economia di scala necessarie per trasformare il “compute orbitale” in un progetto industriale concreto.

Anthropic verserà a Google 200 miliardi di dollari in cinque anni per chip avanzati e capacità cloud

Parallelamente, Anthropic avrebbe firmato con Google uno degli accordi economici più grandi mai visti nel settore tecnologico. Secondo The Information, la società si sarebbe impegnata a spendere fino a 200 miliardi di dollari nei prossimi cinque anni per ottenere accesso a chip avanzati e infrastrutture cloud. L’obiettivo è garantirsi la capacità computazionale necessaria a continuare lo sviluppo dei modelli Claude in un mercato dove la domanda di GPU e server cresce più rapidamente dell’offerta disponibile.

Il valore dell’accordo evidenzia la nuova geografia del potere nell’intelligenza artificiale. Le grandi piattaforme cloud (da Google a Amazon, Microsoft e Oracle) stanno diventando infrastrutture indispensabili per le aziende AI. Secondo le stime riportate, questi operatori avrebbero già accumulato impegni contrattuali vicini ai 2 trilioni di dollari legati alla domanda di servizi AI.

La pressione economica è enorme. Le proiezioni citate indicano che entro il 2026 OpenAI potrebbe sostenere costi server per 45 miliardi di dollari, mentre Anthropic potrebbe arrivare a 20 miliardi. Il problema principale non riguarda più soltanto i chip, ma anche la disponibilità di memoria RAM, energia elettrica e capacità di raffreddamento dei data center.

Questi accordi mostrano come l’intelligenza artificiale stia diventando una questione infrastrutturale globale sempre critica e soprattutto una risorsa strategica scarsa. La competizione non si gioca più solo sui modelli software, ma sulla capacità di assicurarsi supercomputer, energia e accesso privilegiato ai grandi sistemi cloud. Ce ne sarà per tutti?

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https://www.key4biz.it/ai-anthropic-si-garantisce-laccesso-al-supercomputer-di-spacex-e-ai-chip-avanzati-di-google/572166/




Google will invest as much as $40 billion in Anthropic

Google will invest at least $10 billion in Anthropic, and that amount could rise to $40 billion if Anthropic meets certain performance targets, Bloomberg reports.

The investment follows Amazon’s $5 billion initial investment in Anthropic a few days ago; the Amazon deal also leaves the door open to further investment based on performance. Both investments value Anthropic at $350 billion.

Anthropic has seen rapid growth in the use of its Claude models and related products, such as Claude Code, which promises to significantly increase the speed and efficiency with which companies or individuals can develop software. (The reality varies from big improvements to setbacks, depending on the nature of the project and company, how Claude Code is used, and many other factors.)

Several factors contributed to Anthropic’s success in recent months, including controversies around OpenAI and its ChatGPT product and models, more robust agentic workflows, and new products like Claude Cowork, which does some of the same things for general knowledge work tasks as Claude Code does for software development.

https://arstechnica.com/ai/2026/04/google-will-invest-as-much-as-40-billion-in-anthropic/




US accuses China of “industrial-scale” AI theft. China says it’s “slander.”

Specifically, the committee recommended that the State Department assess whether the distillation attacks violate laws like the Economic Espionage Act and the Computer Fraud and Abuse Act. They also want “adversarial distillation” clearly defined and officially categorized as a controlled technology transfer, which would make it easier to restrict fraudulent Chinese access to models.

If such steps were taken, the US could prosecute bad actors and impose heavy financial penalties that might dissuade Chinese firms from treating “serious violations as a tolerable cost of doing business,” the committee’s report said.

China slams accusations as “pure slander”

Kratsios’ memo threatening a crackdown comes ahead of Donald Trump’s highly anticipated meeting with China’s president Xi Jinping next month.

Trump has claimed that the meeting will be “special” and “much will be accomplished.” However, at least one analyst told the South China Morning Post that the war in Iran means that Trump has “lost almost all his bargaining chips” at a time when the US and China are seeking to stabilize a trade relationship that has been tense since Trump took office.

China seems unlikely to tolerate Kratsios’ allegations. Liu Pengyu, a spokesperson for the Chinese embassy in Washington, DC, told FT that the White House accusations were “pure slander.”

“China has always been committed to promoting scientific and technological progress through cooperation and healthy competition,” Pengyu said. “China attaches great importance to the protection of intellectual property rights.”

Whether Trump will side with AI firms that want to see China cut off from their models and sanctioned for distillation attacks has yet to be seen. Trump has, in the past, been accused of making big concessions to China on export control matters that experts have claimed threaten US national security and the economy, as US firms claim the distillation attacks do.

Some of Trump’s concessions may need to be reversed to fight the alleged “industrial espionage.”

Chris McGuire, a technology security expert at the Council on Foreign Relations, told FT that “Chinese AI firms are relying on distillation attacks to offset deficits in AI computing power and illicitly reproduce the core capabilities of US models.” To stop them, the US may need to tighten export controls that Trump loosened, such as allowing Nvidia chip sales to China so long as the US gets a 25 percent cut. That bizarre deal made “no sense” to experts who warned that Trump’s odd move could have opened the door for China to demand access to America’s most advanced AI chips.

https://arstechnica.com/tech-policy/2026/04/us-accuses-china-of-industrial-scale-ai-theft-china-says-its-slander/




Google unveils two new TPUs designed for the “agentic era”

So the new chips allow for faster training, but Google also says you get more useful computation for every volt you pump into a TPU 8t. The company claims a “goodpute” rate of 97 percent, which means less waiting and wasted effort. With better handling of irregular memory access, automatic handling of hardware faults, and real-time telemetry across all connected chips, TPU 8t spends more time actively advancing model training.

When training is done, AI models run in inference mode to generate tokens—that’s the process happening behind the scenes when you tell a model to do something. This doesn’t require as much horsepower, so using the same hardware for both parts of the AI lifecycle is inefficient. That’s why inference is the purview of TPU 8i, which is designed to be more efficient when running multiple specialized agents, with less waiting time. TPU 8i chips also run in larger pods of 1,152 chips versus just 256 for the last-gen Ironwood inference clusters. That works out to 11.6 EFlops per pod, much lower than TPU 8t pods.

TPU 8i chip

The TPU 8i has less raw power than TPU 8t.

Credit: Google

The TPU 8i has less raw power than TPU 8t. Credit: Google

Google has tripled the amount of on-chip SRAM for each TPU 8i to 384 MB. This allows the company’s new chips to keep a larger key value cache on the chip, speeding up models with longer context windows. The eighth-gen AI accelerators are also the first from Google to rely solely on Google’s custom Axion ARM CPU host, featuring one CPU for every two TPUs. In Ironwood, each x86 CPU serviced four TPU chips. Google says this “full-stack” ARM-based approach allows for much greater efficiency.

An efficiency play

It makes sense that efficiency is a core part of Google’s new TPU setup. Training and running frontier AI models is expensive, and the return on investment is unclear. Companies are still burning money on generative AI in the hopes that efficiency will turn the corner at some point. Maybe Google’s new TPUs will help get there and maybe not, but the company has made notable improvements.

https://arstechnica.com/ai/2026/04/google-unveils-two-new-tpus-designed-for-the-agentic-era/




Google unveils two new TPUs designed for the “agentic era”

So the new chips allow for faster training, but Google also says you get more useful computation for every volt you pump into a TPU 8t. The company claims a “goodpute” rate of 97 percent, which means less waiting and wasted effort. With better handling of irregular memory access, automatic handling of hardware faults, and real-time telemetry across all connected chips, TPU 8t spends more time actively advancing model training.

When training is done, AI models run in inference mode to generate tokens—that’s the process happening behind the scenes when you tell a model to do something. This doesn’t require as much horsepower, so using the same hardware for both parts of the AI lifecycle is inefficient. That’s why inference is the purview of TPU 8i, which is designed to be more efficient when running multiple specialized agents, with less waiting time. TPU 8i chips also run in larger pods of 1,152 chips versus just 256 for the last-gen Ironwood inference clusters. That works out to 11.6 EFlops per pod, much lower than TPU 8t pods.

TPU 8i chip

The TPU 8i has less raw power than TPU 8t.

Credit: Google

The TPU 8i has less raw power than TPU 8t. Credit: Google

Google has tripled the amount of on-chip SRAM for each TPU 8i to 384 MB. This allows the company’s new chips to keep a larger key value cache on the chip, speeding up models with longer context windows. The eighth-gen AI accelerators are also the first from Google to rely solely on Google’s custom Axion ARM CPU host, featuring one CPU for every two TPUs. In Ironwood, each x86 CPU serviced four TPU chips. Google says this “full-stack” ARM-based approach allows for much greater efficiency.

An efficiency play

It makes sense that efficiency is a core part of Google’s new TPU setup. Training and running frontier AI models is expensive, and the return on investment is unclear. Companies are still burning money on generative AI in the hopes that efficiency will turn the corner at some point. Maybe Google’s new TPUs will help get there and maybe not, but the company has made notable improvements.

https://arstechnica.com/ai/2026/04/google-unveils-two-new-tpus-designed-for-the-agentic-era/




Pirateria audiovisiva, Canal+ vince contro Cloudflare, Google e Cisco

La Corte d’Appello di Parigi conferma il blocco DNS: gli intermediari devono agire contro la pirateria

La decisione della Corte d’Appello di Parigi segna un passaggio chiave nella lotta alla pirateria digitale in Europa e ridefinisce, con maggiore chiarezza, il ruolo degli intermediari tecnici nella tutela del diritto d’autore. La vittoria giudiziaria ottenuta da Canal+ contro colossi tecnologici come Cisco, Google e Cloudflare non è soltanto un successo per un singolo operatore televisivo, ma rappresenta un precedente destinato a incidere profondamente sull’intero ecosistema digitale.

La vicenda affonda le radici in un problema noto da anni: l’inefficacia relativa delle tradizionali misure di blocco dei siti pirata. In Francia, come in molti altri Paesi europei, i provider di accesso a Internet (ISP) sono già da tempo obbligati a impedire ai propri utenti di raggiungere determinati domini che trasmettono illegalmente eventi sportivi o contenuti protetti.
Queste misure, però, si sono rivelate facilmente aggirabili. È sufficiente modificare le impostazioni del proprio dispositivo e utilizzare un servizio DNS alternativo (come quelli offerti da Google, Cloudflare o Cisco) per bypassare i blocchi imposti dagli operatori locali.

Canal+ vs Big Tech, come si è arrivati a questa sentenza

Proprio per colmare questa lacuna, nel 2024 Canal+ si è rivolta al Tribunale giudiziario di Parigi, ottenendo l’ordine di estendere l’obbligo di blocco anche ai fornitori di DNS pubblici. Il fondamento giuridico di questa richiesta è l’articolo L. 333-10 del Codice dello sport francese, che consente ai titolari dei diritti di chiedere l’adozione di “tutte le misure proporzionate” a qualsiasi soggetto in grado di contribuire a fermare violazioni “gravi e ripetute” dei diritti di sfruttamento.

Cisco, Google e Cloudflare hanno impugnato la decisione, sostenendo che il loro ruolo fosse puramente tecnico e neutrale. Secondo la loro tesi, un servizio DNS si limita a tradurre un nome di dominio in un indirizzo IP, come una sorta di “rubrica telefonica” di Internet, senza alcun coinvolgimento nella distribuzione dei contenuti illegali.
La Corte d’Appello ha però respinto questa impostazione in cinque distinti procedimenti, chiarendo un punto essenziale: la neutralità tecnica non esonera dall’obbligo di cooperare quando un servizio è concretamente in grado di contribuire a fermare una violazione.

I DNS centrali nel blocco dei siti pirata

Nelle motivazioni, i giudici sono stati espliciti: ciò che rileva non è la responsabilità diretta nella pirateria, ma la capacità di impedire l’accesso a contenuti illeciti. I DNS, consentendo agli utenti di raggiungere siti che trasmettono eventi sportivi senza autorizzazione, svolgono un ruolo che può facilitare la violazione dei diritti e, quindi, rientrano nel perimetro degli obblighi previsti dalla legge.

Anche l’argomento dell’inefficacia delle misure è stato respinto. Google aveva evidenziato come i blocchi possano essere aggirati tramite VPN o altri sistemi. La Corte ha ribadito un principio ormai consolidato nel diritto europeo: il fatto che una misura non sia assolutamente efficace non la rende inutile. È sufficiente che contribuisca a ridurre l’accesso illegale, anche solo per una parte degli utenti.

Gli intermediari dovranno implementare i blocchi e sostenere i costi

Particolarmente rilevante è poi il tema dei costi. Cisco ha sostenuto che l’implementazione di un blocco DNS geolocalizzato richiederebbe 64 settimane/uomo di lavoro ingegneristico. I giudici hanno ritenuto questa stima non adeguatamente documentata e, soprattutto, poco credibile alla luce del fatto che la stessa azienda offre già servizi di filtraggio DNS in ambito aziendale. In definitiva, la Corte ha stabilito che gli intermediari dovranno non solo implementare i blocchi, ma anche sostenerne i costi.

Questa decisione assume un’importanza strategica perché rafforza l’idea di una responsabilità diffusa nella filiera digitale. Non si tratta di attribuire colpe, ma di costruire un sistema in cui tutti gli attori (dai provider di accesso ai servizi infrastrutturali) contribuiscano alla tutela dei diritti. È un approccio coerente con l’evoluzione normativa europea, che negli ultimi anni ha progressivamente ampliato gli obblighi di cooperazione degli intermediari.

Sul piano economico, la lotta alla pirateria non è una questione marginale. La trasmissione illegale di eventi sportivi, in particolare, genera perdite significative per broadcaster e detentori dei diritti, mettendo a rischio investimenti, occupazione e sostenibilità del settore. I diritti audiovisivi rappresentano una delle principali fonti di finanziamento per lo sport professionistico: la loro erosione attraverso la pirateria incide direttamente sull’intero sistema.

Una vittoria per Canal+ che ora punta al blocco deli indirizzi IP, una misura che arriverà in Francia entro l’anno

La sentenza della Corte d’Appello di Parigi apre ora la strada a ulteriori sviluppi. Canal+ ha già annunciato che questa vittoria si inserisce in una strategia più ampia, che includerà anche il blocco degli indirizzi IP. In Francia, questa misura dovrebbe essere introdotta entro l’anno, con una prima sperimentazione prevista in occasione del torneo di Roland Garros e un’applicazione su larga scala in vista dei grandi eventi sportivi internazionali.

In parallelo, restano aperti i contenziosi contro i fornitori di VPN, altro anello cruciale nella catena della distribuzione illegale. Se anche questi dovessero essere coinvolti in obblighi di blocco, il modello francese potrebbe diventare un riferimento per altri Paesi europei.

In definitiva, la decisione di Parigi segna un cambio di paradigma: la lotta alla pirateria non si limita più ai soli fornitori di accesso, ma si estende a tutti i soggetti che, anche indirettamente, rendono possibile l’accesso ai contenuti illegali. Un principio destinato a ridefinire gli equilibri tra libertà della rete, innovazione tecnologica e tutela dei diritti.

Leggi le altre notizie sull’home page di Key4biz

https://www.key4biz.it/pirateria-audiovisiva-canal-vince-contro-cloudflare-google-e-cisco/570002/




Google releases new apps for Windows and MacOS

The first Gemini desktop app, now on Mac

There’s currently no Google search app for macOS, but Google has the AI side covered with the new Gemini app. This is the company’s first standalone desktop app for accessing Gemini. Google’s Josh Woodward says Google has been getting requests for a native Mac app, so the company put together a small team to build one. It didn’t even take very long, with less than 100 days to deliver a supposed 100-plus features on Mac. CEO Sundar Pichai says it was built entirely using Google Antigravity.

Opening the app is similar to how you access the Windows search app—hit Option + Space at any time to pull up a Gemini prompt bar. You can ask general questions like you would the web version of Gemini, but it can also access your windows for additional context. Again, that’s similar to the Windows app, with a greater focus on AI.

Gemini app on Mac

Gemini for Mac has just about every feature of Gemini on the web.

Credit: Google

Gemini for Mac has just about every feature of Gemini on the web. Credit: Google

The Mac Gemini app, which is coded entirely in Swift, includes a full spate of Gemini features and model types. You can upload files, create notebooks, and access tools like Deep Research and Canvas right on your desktop. It also has access to image-, video-, and music-generation models. More features are apparently on the way, too.

Even if you like generative AI, Google’s method of distribution may be a dealbreaker. As of now, the company has opted not to list the app in the App Store for Mac. Instead, you have to download and install a DMG file from Google’s website. This one is available in all regions and languages with Gemini support.

https://arstechnica.com/gadgets/2026/04/google-launches-search-app-for-windows-gemini-app-for-mac/




Boston Dynamics’ robot dog now reads gauges and thermometers with Google’s AI

Robots such as Boston Dynamics’ four-legged Spot can now accurately read analog thermometers and pressure gauges while roaming around factories and warehouses. Those improvements come courtesy of Google DeepMind’s newest robotic AI model that aims to enhance robotic capabilities for ‘embodied reasoning’ when interacting with physical environments.

The new Gemini Robotics-ER 1.6 model announced on April 14 performs as a “high-level reasoning model for a robot” that can plan and execute tasks, according to Google DeepMind. This model also unlocks the capability of accurately reading instruments such as complex gauges and doing visual inspections using sight glasses that provide a transparent window to peek inside tanks and pipes—a performance upgrade that came about through Google DeepMind’s ongoing collaboration with robotics company Boston Dynamics.

Boston Dynamics has a keen interest in testing both quadruped and humanoid robotic workers in a wide range of industrial facilities, including the automotive factories of the robotic company’s corporate owner, Hyundai Motor Group. The company’s robot “dog,” Spot, is being trialled as a robotic inspector that roams throughout industrial facilities to check up on everything. Such inspection duties require “complex visual reasoning” to interpret the multiple needles, liquid levels, container boundaries and tick marks, along with text, in various instruments.

The model driving it

To handle such tasks, the Gemini Robotics-ER 1.6 model provides robots with “agentic vision” that combines visual reasoning with the capability of executing code to create a “visual scratchpad” for inspecting and manipulating images. Such agentic vision was introduced in Google’s Gemini 3.0 Flash model back in January 2026.

The agentic vision capability reportedly boosts robotic performance on instrument reading tasks from 23 percent in the older Gemini Robotics-ER 1.5 model to 98 percent in the new Gemini Robotics-ER 1.6 model. For comparison, Gemini 3.0 Flash delivered just 67 percent accuracy.

The baseline Gemini Robotics-ER 1.6 model can still achieve 86 percent accuracy in reading instruments even without agentic vision. That is because the model uses a process of pointing to different elements in a visual image to process complex tasks, such as counting items or identifying the most salient features. It also supposedly delivers an improved “multi-view reasoning” capability that allows a robotic system to use multiple camera streams to better understand its environment.

https://arstechnica.com/ai/2026/04/robot-dogs-now-read-gauges-and-thermometers-using-google-gemini/