[AI DAILY NEWS RUNDOWN] OpenAI’s Phone, Home Data Centers, and PayPal AI Layoffs (May 06 2026)

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Summary: In today’s briefing, we analyze the “Decentralization of Intelligence.” We deconstruct OpenAI fast-tracking a custom-built AI smartphone to control the hardware layer, and Apple paying $250M to settle a class action over delayed AI Siri features. We explore the radical shift in compute infrastructure, highlighted by Nvidia and Span mounting liquid-cooled mini AI data centers on the exterior walls of residential homes. We also cover OpenAI’s new MRC networking protocol designed to stretch GPU compute, Anthropic’s new finance agents, publishers suing Mark Zuckerberg personally for piracy, and PayPal joining Coinbase in massive, AI-driven workforce layoffs.

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Important Topics:

• OpenAI Fast-Tracks Smartphone: OpenAI partners with MediaTek to mass-produce an AI agent phone by 2027, projecting 30 million units by 2028.

• Apple’s $250M AI Settlement: Apple agrees to pay $250M to iPhone users over the delayed rollout of “personalized Siri” features heavily promoted in 2024.

• Home-Based Mini Data Centers: Startup Span teams with Nvidia to mount liquid-cooled XFRA compute nodes on residential homes, bypassing centralized grid strain.

• OpenAI’s MRC Compute Protocol: OpenAI open-sources the Multipath Reliable Connection protocol, using “packet spraying” to prevent massive GPU cluster failures.

  

• PayPal Cuts 20% of Staff: Following Coinbase’s 14% reduction, PayPal announces plans to cut one in five workers to capitalize on AI-driven productivity gains.

• Publishers Sue Zuckerberg: Five major book publishers launch a class-action lawsuit accusing Meta and Mark Zuckerberg personally of AI book piracy.

• Google’s “Remy” Agent: Google is internally testing Remy, a 24/7 autonomous AI assistant built deeply into the Gemini ecosystem to rival OpenAI’s OpenClaw.

• GPT-5.5 Instant & Quantum Bio: OpenAI launches GPT-5.5 Instant to reduce hallucinations, while IBM uses quantum computing to simulate 12,000-atom protein complexes.

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Apple pays $250M over Siri AI delays

• Apple has agreed to pay $250 million to settle a class action lawsuit over its delayed rollout of the “more personalized Siri” features that were first shown at WWDC 2024, without admitting any wrongdoing.

• The settlement works out to about $25 per eligible device bought in the US between June 10, 2024 and March 29, 2025, though payouts could climb as high as $95 depending on claim numbers.

• The lawsuit accused Apple of promoting AI features “that did not exist at the time, do not exist now, and will not exist for two or more years,” saturating airwaves to build consumer expectations around the iPhone’s release.

  Smartphone 101 - Pick a smartphone for me - android or iOS - Apple iPhone or Samsung Galaxy or Huawei or Xaomi or Google Pixel
  

OpenAI plans 30 million phones in two years

• OpenAI is fast-tracking an “AI agent phone” and could begin mass production in early 2027, with analyst Ming-Chi Kuo predicting 30 million units will be built between 2027 and 2028 if plans hold.

• The device will run on a customized version of MediaTek’s Dimensity 9600 chipset, with Kuo saying MediaTek will likely be the sole processor supplier, while Qualcomm and Luxshare are also working with OpenAI.

• Kuo said the phone will use a dual-NPU architecture for heterogeneous AI compute, splitting tasks like image enhancement and object detection between two AI processors, plus an image signal processor with enhanced high dynamic range.

OpenAI unveils protocol to stretch compute

From the Deep View

OpenAI is getting creative to deal with the industry’s imminent compute crunch.

On Wednesday, the ChatGPT maker and a coalition of researchers from Microsoft, AMD, Broadcom, Nvidia, and Intel published a paper offering a rare look into company’s training stack, debuting a new compute networking protocol designed to make GPU clusters faster, more reliable and conserve precious compute cycles.

The protocol, which has been in the works for two years, is instrumental in OpenAI scaling the compute that it needs to continue building bigger and better models, noting in a blog post that the networking approach accelerates its vision for Stargate, the company’s long-term effort to garner the compute it needs to build and scale cutting-edge AI.

The paper introduces a protocol called MRC, or Multipath Reliable Connection, which essentially tackles two main issues with the networks that serve as the connective tissue of AI infrastructure: Congestion and failures, Mark Handley, OpenAI’s networking lead, told me. As GPU clusters grow, these are problems that become more arduous to solve.

• This protocol relies on “packet spraying,” said Handley, which essentially scatters data along hundreds of paths in the network simultaneously to prevent any one network link from getting congested. This also reduces the amount of “tiers” in a GPU cluster, resulting in “flatter” networks that use up less of the data center’s compute and power.

• When handling network failures, MRC detects and reroutes when paths go down in microseconds. This allows GPU clusters to continue training seamlessly, even if parts of the network break down.

• Additionally, the MRC pairs with a protocol called SRv6, or IPv6 Segment Routing, which essentially tells data the exact path it needs to take through a network, rather than forcing the network switches to do the routing work themselves, further reducing the energy requirements of these switches and the data center more broadly.

“We want to use as much compute as we can get, but also we want to make sure that we’re using it efficiently and effectively, and this is a critical component of that,” Greg Steinbrecher, OpenAI’s workload lead, told The Deep View in an exclusive interview.

The protocol is already in use in OpenAI and Microsoft’s largest training clusters, including the Oracle site in Abilene, Texas, and in Microsoft’s Fairwater supercomputers, and has been used to train GPT-5.5 and other models.

When implemented, this new protocol introduces several major downstream advantages, Steinbrecher told me. Conventional, large-scale AI training jobs are a “failure amplifier” for GPU clusters, he said: If one thing goes wrong, the ripple effect forces the process to grind to a halt, leaving GPUs to sit idle. Network congestion, additionally, slows the rate at which researchers can innovate.

MRC circumvents these issues, allowing OpenAI to “turn the crank on our entire research pipeline much faster,” Steinbrecher said. “That allows us to make better use of the resources that we have.”

The MRC specification is available through the Open Compute Project under an open license. Steinbrecher emphasized the importance of this, claiming that this protocol is not one in which OpenAI is trying to “differentiate,” but rather move the entire industry past what they consider a legacy bottleneck. Handley said that the infrastructure industry has reached a point where it’s worth establishing open standards, “as opposed to each of these large companies doing their own thing.”

“Several players in the industry have their own in-house implementations of protocols … that type of market fragmentation is bad for the networking industry,” Steinbrecher said. “You want everyone’s energy going in one direction and pushing together, and then everyone moves faster as a result.”

Quantum, AI spur biological breakthroughs

From the Deep View

For years, IBM has been at the forefront of quantum computing. At this year’s Think conference, that ambition was on full display.

During the opening keynote, IBM CEO and Chairman Arvind Krishna highlighted quantum’s potential with the technology having the capability to unlock new discoveries at an incredibly quick pace — including AI developments.

“Quantum can help uncover what AI cannot yet compute, then AI learns from the quantum and can make faster and faster progress on algorithms and on computations to give you a state of where we are,” said Krishna.

To showcase the tangible use cases of quantum computing, IBM highlighted a biological research milestone achieved with the Cleveland Clinic and Riken: using two of the IBM quantum computers and two of the world’s most powerful supercomputers, the companies were able to simulate protein complexes spanning up to 12,635 atoms. In October 2024, it was only able to simulate 10.

• This is important, as the molecules in your body are proteins, or the “workhorse in the cell” that allow people to exist every day, as Serpil Erzurum, EVP and chief research and academic officer at the Cleveland Clinic’s Lerner Research Institute, explained during the keynote.

• Understanding the 3D structure and motion of a protein is key in biological research, as it helps researchers understand how a drug candidate could bind to a protein and develop effective drugs. Yet, it has remained a challenge as classical computers can only approximate solutions. Erzurum emphasizes that this development is “a moment.”

“Everyone will want to see what these structures look like to understand biology, disease, what’s going wrong if it’s not working, and more importantly, what can I make to fit into the three dimensional structure, to change the structure of that protein–because that’s therapy, and that can make a difference in life,” said Erzurum.

Another example Erzurum noted is using quantum computing and machine learning to dramatically speed up the identification of which treatments a harmful microbe is sensitive to, potentially saving lives given that infections remain a leading cause of death globally.

In a separate Q&A with analysts and select press, Krishna did make it clear that in the next three years, he does not see quantum as replacing either AI or classic CPUs, but rather it will solve problems the two cannot solve, such as the modeling molecules example.

ChatGPT accuracy improves in new model push

From The Deep View

OpenAI’s Instant model, the lightweight option available to everyday users, just got an upgrade.

On Tuesday, OpenAI launched GPT-5.5 Instant, which was updated to be more reliable, with the company claiming it boasts “significant improvements in factuality across the board.” This claim is particularly notable given that it is the default model for its hundreds of millions of daily users.

Benchmark performance shows that GPT-5.5 Instant outperforms GPT-5.3 Instant, the model currently used in ChatGPT, across multimodal reasoning, document parsing, and science and math evaluations. In everyday performance, OpenAI says the updates mean that users experience:

• Less hallucinations: GPT-5.5 Instant produces 52.5% fewer hallucinated claims than GPT-5.3 Instant on high-stakes prompts in areas like medicine, law, and finance and inaccurate claim reduction by 37.3% on challenging conversations users had flagged for factual errors

• More capable: The model is generally smarter and more capable across photo and image models, STEM questions, and choosing when to fetch information from the web

• Tighter responses: More to the point responses that don’t lose substance

• More personalization: It is more effective at using context from either past chats or connected files and Gmail by being faster at searching past conversations. This is rolling out to Plus and Pro users on the web, and coming soon to mobile. It will expand to more plans in the coming weeks

OpenAI also introduced memory sources across all ChatGPT models, which give users the ability to see the context used to personalize their responses and then delete or correct it if something is outdated or not wanted to be cited. Essentially, it’s giving users more control of how their past chats are used and referenced.

The memory sources feature is rolling out to all consumer plans on the web and soon on mobile. GPT-5.5 Instant is rolling out to all ChatGPT users, replacing GPT-5.3 Instant as the default model, while paid users can still access GPT-5.3 Instant for three months before being retired. It is also available in the API as “chat-latest.”

Apple opens iOS 27 to rival AI models

• Apple will let iPhone, iPad, and Mac owners pick from several outside AI models to run features built into iOS 27, iPadOS 27, and macOS 27, with the shift planned for this fall, according to people familiar with the matter.

• The third-party AI services will handle tasks like generating and editing text and images across Apple’s software, expanding the company’s strategy to turn its devices into a broad AI platform rather than relying on a single provider.

• The sources who described the plans asked not to be identified because the details are private, and the article does not name which outside AI models Apple intends to offer users when the new operating systems ship.

Publishers sue Meta over AI book piracy

• Five book publishers — Hachette, Macmillan, McGraw Hill, Elsevier, and Cengage — along with author Scott Turow, have filed a class action lawsuit accusing Meta and Mark Zuckerberg of pirating copyrighted books to train the Llama AI platform.

• The complaint claims Zuckerberg personally authorized and encouraged the infringement, saying Meta reproduced and distributed millions of copyrighted works without permission or compensation, knowing the conduct violated copyright law.

• Meta spokesperson Dave Arnold pointed to past rulings that training AI on copyrighted material can qualify as fair use, echoing a recent Anthropic case where a judge rejected copyright infringement but floated piracy as a separate path to damages.

Google tests Remy 24/7 AI agent

• Google is testing an AI agent codenamed Remy that aims to turn the Gemini app into a 24/7 personal assistant for work, school, and daily life by taking actions on a user’s behalf.

• According to Business Insider, Remy is built deep into Google’s ecosystem and can monitor things that matter to users, handle complex tasks proactively, and learn preferences over time, positioning it against OpenClaw, which OpenAI acquired.

• Remy is currently in a “dogfooding” stage with employees testing it internally, and while no launch date is set, Google’s I/O event on May 19-20 could serve as the debut for the new agent.

OpenAI launches GPT-5.5 Instant for ChatGPT

• OpenAI has rolled out GPT-5.5 Instant as the new default model in ChatGPT, replacing GPT-5.3 Instant, with the company saying it cuts down hallucinations in sensitive fields like law, medicine, and finance while keeping low latency.

• The model scored 81.2 on the AIME 2025 math test versus 65.4 for the older version, and hit 76 on the MMMU-Pro multimodal reasoning benchmark compared to the predecessor’s 69.2.

• GPT-5.5 Instant can pull from past conversations, files, and Gmail for personalized answers, starting on web for Plus and Pro users, and ChatGPT will now show memory sources that users can delete or correct across all models.

OpenAI fast-tracks ‘AI agent phone’

The Rundown: OpenAI is reportedly accelerating development of its first AI phone, now aiming for mass production in the first half of 2027, which is a full year earlier than previously reported, according to supply chain analyst Ming-Chi Kuo.

The details:

• Kuo says the timeline shift is likely driven by OAI’s IPO ambitions (strong hardware could strengthen investor pitch) and rising competition in AI phones.

• The phone’s standout spec will be its image signal processor, with an enhanced HDR pipeline to improve AI agents’ real-world visual sensing.

• MediaTek is positioned to be the sole chip supplier, with the device using two AI processors to handle vision and language tasks simultaneously.

• Kuo also added that OpenAI’s combined 2027–28 shipments of this phone could touch 30M, if the development stays on track.

Why it matters: Controlling hardware and OS could be the key to a true agentic phone. But if OpenAI’s AI phone is closer than we thought, where does this leave the device it’s building with Jony Ive’s io? OpenAI acquired io last year with much fanfare to go “beyond screens,” but nothing concrete has appeared so far except a few rumors.

Anthropic’s AI agents for finance work

Image source: Anthropic

Anthropic just unveiled 10 ready-to-run AI agents aimed squarely at financial services and insurance — capable of handling work ranging from building pitchbooks and screening KYC files to reviewing earnings and valuations.

The details:

• Each agent comes with task-specific domain skills and instructions, connectors to relevant data sources, and add-on Claude models for sub-tasks.

• Firms can adapt any agent of their choice to their own modeling conventions, risk policies, and approval flows — while staying in the loop 24/7.

• The agents can be used as plugins within Claude Cowork or Claude Code on desktop, or as cookbooks, running as Managed Agents on the Claude platform.

• Claude is also getting an add-in for Microsoft 365 as well as data connectors from Dun & Bradstreet, Verisk, IBISWorld, and other financial services partners.

Why it matters: Development, cybersecurity, design, and now finance. Anthropic is going domain by domain, meeting businesses where they are instead of selling a general model and letting them figure it out. Its new $1.5B joint venture alongside Wall Street giants reinforces this strategy, further fueling its race with OpenAI.

Home-based ‘mini’ AI data centers are coming

California startup Span is teaming up with Nvidia to install mini AI data centers on the walls of residential homes and small businesses, tapping unused electrical capacity on local grids to meet surging AI compute demand.

The details:

• Span has developed XFRA, small compute nodes that mount on the exterior walls of homes, alongside accompanying HVAC and electrical systems.

• Nvidia is providing its liquid-cooled RTX PRO 6000 Blackwell Server Edition GPUs to power each XFRA box, ensuring noiseless computing for AI workloads.

• Span told CNBC it can install 8,000 XFRA units 6x faster and at one-fifth the cost of building a comparable 100MW centralized data center facility.

• Currently, the company is working with PulteGroup, one of the largest U.S. homebuilders, to test the box and its economics in newly built communities.

Why it matters: Grid strain from data centers is real, and Span’s boxes could spread the load while tapping only unused capacity. But public response is an open question — not all will love the idea of a data center box mounted where kids play, especially when alternatives like ocean– and space-based data centers are also in sight.

Google wants you to use local AI:

Chrome users are annoyed that Google is installing the Gemini Nano AI model on their machines. Google protested the protests, saying that it has “offered Gemini Nano for Chrome since 2024 as a lightweight, on-device model [that] powers important security capabilities like scam detection and developer APIs without sending your data to the cloud.” Not enough to silence critics, but at least you can turn the feature off.

DeepSeek set could raise $4B:

Chinese AI lab DeepSeek, fresh off the release of its V4 Pro model, is looking to close a massive funding round. With $3 to $4 billion potentially coming its way, the well-known AI model maker could earn a valuation as high as $50 billion in the raise. While DeepSeek is looking to raise more private capital (including cash from China’s national AI fund), two of its rivals (Z.ai and MiniMax) went public earlier this year. DeepSeek, follow suit.

Tech layoffs keep coming:

After American crypto giant announced it would excise 14% of its humans, fintech behemoth PayPal has plans to delete around 20% of its own staff. That’s one in seven workers from Coinbase gone overnight, and one in five from PayPal over the next few years. Why is PayPal pursuing such stark layoffs? It wants faster decision-making and to take advantage of AI-driven productivity gains. Sounds familiar!

What Else Happened in AI on May 06th 2026?

OpenAI’s GPT-5.5-Instant started rolling out to all ChatGPT users, bringing improved performance, stronger memory, and more personalized, concise responses.

Microsoft expanded its Copilot Cowork agentic system to iOS and Android, while adding built-in skills for common tasks and data plugins for business systems.

Apple agreed to pay some U.S. iPhone buyers a collective $250M to settle a class action lawsuit over misleading claims about its new AI Siri, but admitted no wrongdoing.

Perplexity AI launched Computer for Professional Finance, bringing licensed data and 35 dedicated workflows to its agentic system to help analysts handle routine work.

Anthropic reportedly committed to spending $200B on Google’s cloud and chips over the next five years, now making 40%+ of Google’s revenue backlog.

Coinbase CEO Brian Armstrong said the company is cutting 14% of its workforce, ~700 people, as it shifts to AI-native teams, agent-driven workflows, and leaner ops.