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Cancel ChatGPT and get lifetime access to Claude, Gemini, and more for $55.30 with this code
No monthly subscription fees, and it'll even let you send one prompt to multiple AI models.
Karlie Kloss attends Taylor Swift and Travis Kelce's wedding a decade after reported falling out
Karlie Kloss and her husband, Joshua Kushner, attended Taylor Swift and Travis Kelce's wedding at Madison Square Garden a decade after rumors swirled that the singer and the supermodel had a falling out.
iPhone 18 With 9GB RAM Still Won't Support Two New iOS 27 Features
The lower-end iPhone 18 and iPhone 18e will be equipped with 9GB of RAM, up from 8GB in the iPhone 17 and iPhone 17e, according to supply chain analyst Ming-Chi Kuo. In a social media post, Kuo said the 1GB increase in RAM will ensure that Apple Intelligence features continue to run smoothly on the pair of devices. The higher-end iPhone 18 Pro, iPhone 18 Pro Max, and foldable "iPhone Ultra" will each have the same 12GB of RAM as the iPhone 17 Pro models, added Kuo.
Amazon quietly updated 2023’s Fire HD 10 tablet with 4GB of RAM
The 32GB model is now available with a bump from 3GB to 4GB of RAM with a small price increase.
Britney Spears' sons say mom was 'nervous' about their modeling debut
A mother's positive affirmation goes a long way, especially when it's coming from Britney Spears.
If this game-changing Galaxy S27 leak is real, nobody's gonna stop me from buying it
Samsung could offer an ultra-exclusive feature to the vanilla model.
Founder shares AI lesson after foreign Fable access returned
A UK founder said losing access to Anthropic's Fable AI model taught him to always have a backup plan when building with AI.
Why One Global Shipping Choke Point Isn’t a Blueprint for Another
The Strait of Malacca may be a model for how Oman and Iran could collect fees in the Strait of Hormuz, but the differences between the waterways are vast.
Apple Responds to Lawsuit Filed by Three YouTube Channels
Earlier this year, three YouTube channels sued Apple, alleging that the company violated the U.S. Digital Millennium Copyright Act (DMCA) by unlawfully accessing and scraping millions of copyrighted YouTube videos to train its AI models. In a class action lawsuit filed with the U.S.
Claude Fable 5 isn’t permanently leaving subscriptions, Anthropic says
Anthropic says Claude Fable 5 won't be accessible via Claude subscriptions after July 7, but it's not a permanent change, and the company expects the model to return outside the usage-based plan soon.
Meta's Watermelon AI model has caught up to GPT-5.5, Alexandr Wang says
Meta's superintelligence chief says its upcoming Watermelon model now matches GPT-5.5 on key AI benchmarks.
Legacy Business Spotlight: Baton Rouge Clinic
— ESTABLISHED 1946— The Baton Rouge Clinic, AMC has been delivering patient-centered care to the Capital Region for 80 years. Founded by four local physicians, the clinic has grown from a single practice into a network of 18 locations serving nearly 400,000 patients across Louisiana, while remaining true to the physician-led model thathas defined it […]
Could your gut bacteria really slow Alzheimer’s? Scientists reveal a surprising link - Futura-Sciences
European researchers previously demonstrated that transferring stool samples from human Alzheimer’s patients into healthy rats triggered symptoms like spatial memory issues. Other models show that altering gut microbes changes the buildup of amyloid plaques and tau proteins, the two main hallmarks of the disease. Scientists have even found that certain...
iPhone 18 Pro Could Use Qualcomm Modem in the US and C2 Elsewhere
Stolen data from Apple manufacturing partner Tata Electronics appears to reveal that the iPhone 18 Pro will use different modem chips depending on the market it is sold in, with U.S. models retaining Qualcomm hardware while international models will feature Apple's in-house C2 modem. The finding emerged from a wide-ranging cyberattack on Tata, which alongside Foxconn assembles the iPhone.
Team's prediction task compares GPT-4o with classic machine learning
Large language models have been functionally opaque. Seeking transparency, a team undertook a comparison with traditional machine learning.
MacBook Pro models sharing the MacBook Ultra redesign is, and isn't, surprising
We’ve been hearing for a long time now that a new high-end MacBook Ultra model with a touchscreen will get...
The Business Model of Colleges Is Broken. It’s About to Get Worse
Declining enrollment and Trump’s policies are “breaking the business model that built the modern higher education system,” writes Jeffrey Selingo.
Apple reportedly orders 10M foldable iPhone Ultra models, which could sell for around $2500
Apple plans to manufacture and sell around 10 million foldable iPhone Ultra models, according to a new report. That’s roughly...
Apple to launch 5 new iPhone models to gain market share amid memory crunch
Company raises production target for first foldable phone to about 10 million units
Meta stock soars as Mark Zuckerberg explores cloud business
Meta shares soared Wednesday on a report that the company is wading into the business of selling cloud computing services and access to AI models.
Operations workforce powers ORNL’s autonomous science future
Behind every self-driving laboratory at the Department of Energy’s Oak Ridge National Laboratory is a team people most never see. Facilities and Operations workers are building and maintaining the infrastructure that makes autonomous science possible. More than a dozen self-driving labs operate at ORNL, placing the Tennessee national lab among the first research institutions in the world to create this autonomous laboratory model at scale.
Meta Plans Cloud Business to Take on Big Tech Rivals
Meta is planning a cloud infrastructure business that will sell AI computing power/model access. That’s according to a report Wednesday (July 1) by
WHO Health Emergencies EPI-WIN webinar: Strengthening the governance of national public health agencies for emergency preparedness and response
This webinar will provide a platform to present the main findings of the cross-country study on governance of National Public Health Agencies for emergency preparedness and response and bring country perspectives from different governance models on how governance arrangements shape emergency action in practice.
Apple’s iPhone 18 Pro Max eSIM Model To Pack A Mammoth 5,425mAh Battery, While Physical SIM Buyers Get Predictably Shortchanged On Battery Capacity
In keeping with the prevailing divulgatory trend, the latest tidbit has detailed the battery capacity within Apple's iPhone 18 Pro Max.
CMS proposes updates to home health payments for CY 2027, updates to provider enrollment and quality and value-based purchasing programs
The Centers for Medicare & Medicaid Services July 1 issued its calendar year 2027 proposed rule for the home health prospective payment system. The rule proposes a 2.4% update, which includes a 3.1% market basket update, reduced by a 1.0 percentage point cut for productivity, as well as an 0.3 percentage point increase related to outlier payments. In addition, the agency proposes a temporary cut of 3.0% that it states is necessary to achieve budget-neutral implementation of the Patient-driven Groupings Model.
Alex Karp says AI models are 'irresponsibly oversold'
Palantir CEO Alex Karp said that "something has gone completely wrong" in the AI market. "The enterprises are just tired of it," he said.
The moment Anthropic convinced me it’s serious about science
AI Prognosis: The release of Claude Science suggests big model makers are getting serious about real science, and not just flashy problems.
Anthropic launches Claude Science AI workbench for researchers
Claude Science connects more than 60 databases and tools in one environment, running on existing Claude models with no specialized biology training
ACCESS Model: behavioral health edition
A new value-based care program for chronic condition management begins July 5. | A new payment model is designed to pay digital health companies based on outcomes in chronic condition management. But where does behavioral health fit? This episode explores that question with SonderMind and Headspace, two companies participating in the model's behavioral health track.
Meta building cloud business to sell excess AI computing capacity
The company is weighing plans to sell access to AI models and raw computing capacity, setting up new competition with AWS, Azure, and Google Cloud
Content Independence Day, one year on: building the business model for the agentic Internet
One year after declaring Content Independence Day, a dynamic market for monetized content has officially emerged. In this report, we examine how the rise of autonomous AI agents is upending traditional search referrals and detail the new infrastructure required to support a sustainable web economy.
Meta Is Building a Cloud Business to Sell Excess AI Compute
Meta Platforms Inc. is developing plans for a cloud infrastructure business that will sell access to AI computing power and models, setting up a new vector of competition with industry leaders like Amazon Web Services, Microsoft Azure and Google Cloud.
The Download: Anthropic launches Claude Science, and California’s carbon manure math
Plus: The US has lifted restrictions on Anthropic’s Mythos and Fable models.
Smart voices in tech react to return of Anthropic's Fable and Mythos
Anthropic restores Fable 5 AI model after the Trump administration lifted export controls. Here's what people in tech are saying about the saga.
Trump administration lifts Claude Mythos 5, Fable 5 export restrictions after Anthropic works with government
The Commerce Department lifted export restrictions on Anthropic's Claude Fable 5 and Mythos 5 after a review, clearing the models for wider access
Claude Science is Here, Antibiotics Designed by Text Prompt Among Applications
Basecamp Research’s antibiotic design and vaccine prediction AI models are now available through Anthropic’s Claude Science.
Generative AI chest X-ray models offer new approach to radiology reporting and quality improvement
While the technology remains investigational in many practices, researchers say it has the potential to improve diagnostic accuracy, streamline AI development and strengthen radiology quality assurance.
iPhone 18 Pro leaks: Qualcomm or Apple C2 model, A20 details, camera upgrades
After a closer look at some new data, Apple's iPhone 18 Pro modem situation may not be cut-and-dried. Here's what the latest leaks say is in store for cellular connectivity, the A20 chip, and possible camera improvements.
Google introduces a faster, cheaper image generator with Nano Banana 2 Lite
Google is updating its image generator to make it faster and cheaper, making it a more useful tool for creators looking to make AI content.
Google's new Nano Banana 2 Lite image model is its fastest and cheapest yet
They may not look as good, but Nano Banana 2 Lite images only take a few seconds to create.
Anthropic’s Claude Science bets on workflow, not a new model, to win over scientists
Anthropic's Claude Science is a workbench that gives scientists one environment to do computational research, saving them from the need to bounce between databases, pipelines, and tools.
Anthropic releases Claude Science, a product aimed at researchers, the pharma industry
Anthropic released Claude Science, an application that optimizes its large language model for scientists and, especially, those doing research at pharma companies.
Basecamp Research brings EDEN's antibiotic and vaccine design models to Claude Science
/PRNewswire/ -- Basecamp Research today announced that its antibiotic design and vaccine target prediction EDEN models are now available through Claude,...
NC budget includes UNC, NC State athletics for sports betting tax distribution
The state’s two major universities were left out of the previous model, which provided tax revenue to college athletic programs.
Report: Apple Watch Redesign Coming Next Year With New Band System
A "major overhaul" of the Apple Watch's design is due to arrive next year with a new system for connecting bands, according to a known Weibo leaker. In a set of recent posts, the leaker known as "Instant Digital" linked the new claim to older rumors about an "Apple Watch X" model, which was said to introduce a fresh design and break compatibility with the existing watch band system.
Alleged iPhone 18 Pro Sim Tray Again Shows Dark Cherry Color
Apple's upcoming iPhone 18 Pro models are expected to introduce new color options, including a dark cherry color, and today we may have been given another peek at the rumored finish, courtesy of the Chinese leaker known as Ice Universe. Image shared by leaker Ice Universe In an image posted on Weibo, a SIM tray allegedly from the unreleased iPhone is shown in a dark cherry colour, which could also be described in this grainy example as burgundy, brownish, or purple.
New Switch 2 model spotted in the wild with updated screen
It looks like a new version of Switch 2 with an updated LCD screen is rolling out soon…
Cara Delevingne confirms she and Amber Heard were romantically involved amid actress' Johnny Depp divorce
Model-actress Cara Delevingne confirms she and 'London Fields' costar Amber Heard were romantically involved amid actress' divorce from Johnny Depp.
Dbrand Forced To Pull Steam Machine Companion Cube
Mere after the reveal of the Valve Steam Machine, accessory maker Dbrand announced that it was releasing the "Companion Cube," a Steam Machine accessory that was modelled after the Portal weighted companion cube storage box. Following massive interest in the Companion Cube in the week since its anno...
Evidence points to potential new LCD screen for Nintendo Switch 2
The Nintendo Switch 2 screen could be getting a revision, based on the latest evidence. On a Chinese resale site, a listing recently appeared for a a new model of the system’s LCD panel. Sharp would apparently behind the updated screen. The current Nintendo Switch 2 features a panel from Innolux. This new screen has a different circuit, connector, and...
Apple Releases iOS 26.5.2 With Security Fixes
Apple today released iOS 26.5.2 and iPadOS 26.5.2, minor updates to the iOS and iPadOS 26 operating systems that came out in September. iOS 26.5.2 comes a month after the launch of iOS 26.5.1, an update that added a charging fix for the iPhone Air and iPhone 17 models. iOS 26.5.2 and iPadOS 26.5.2 can be downloaded on eligible iPhones and iPads over-the-air by going to Settings > General > Software Update.
Databricks and Nvidia Launch Genesis Workbench for AI Scientists
AI is becoming an increasingly important tool for drug discovery. However, for many pharmaceutical and biotech companies, the challenge isn’t finding more powerful models. It’s getting existing models to work […]
Leaker outlines iPhone lineup for next year, with six new models coming
Apple is rumored to have more new iPhones launching in 2027 than ever before, here’s every model coming per leaker Digital Chat Station.
Millions of exploding stars could soon reveal dark energy's secrets
A new AI-powered framework could transform how astronomers measure the expansion of the Universe. By analyzing images of Type Ia supernovae and modeling their environments in unprecedented detail, researchers can estimate cosmic distances with near-spectroscopic accuracy. The technique is designed for the flood of data expected from the upcoming Vera C. Rubin Observatory and may greatly improve our understanding of dark energy.
Leaked A20 Pro Image Hints at iPhone 18 Pro Performance Gains
An alleged image of the iPhone 18 Pro motherboard has leaked online, showing the A20 Pro chip will use a new packaging technology that should offer notable performance gains over the previous model. The leaked image, which has been shared by the accounts "WHYLAB" and "Ice Universe" on Weibo, appears to show the A20 Pro chip integrated into TSMC's new packaging architecture, known as Wafer-Level Multi-Chip Module (WMCM) technology.
Cheaper AI is better: Soaring bills are reshaping how businesses choose models
Silicon Valley's powerful and pricey AI models have been a necessity for businesses looking to future-proof themselves. But now a growing number of tech CEOs are arguing that cheaper options would be crucial for their wider adoption.
Google Cloud to Offer Specialist AI Models for Science Research
Alphabet Inc.’s Google will start offering specialist artificial intelligence models from software company SandboxAQ through its cloud service, expanding enterprise and research access to technology designed to accelerate drug discovery, materials science and semiconductor manufacturing.
iPhone 18e Won't Get ProMotion Display, Says Leaker
Apple's upcoming iPhone 18e will have the same display refresh rate as the existing iPhone 17e, according to a prominent Chinese leaker. Discussing Apple's product plans for 2027 in a Weibo post, Digital Chat Station claimed that the next generation of Apple's low-cost iPhone will feature the same 60Hz low-temperature polycrystalline silicon (LTPS) TFT panel as the current model.
Benchmark Scores Don’t Break. Clinical Reality Does. The Health AI Readiness Illusion.
Nature Medicine's frontier AI evaluation exposes a dangerous gap: models acing medical benchmarks collapse under adversarial pressure, and the FDA has no…
Coinbase's CEO outlined 5 strategies to keep AI spend low
One of his strategies was experimenting with using cheaper Chinese LLMs as default models.
Entertainment Firms Face AI Copyright Uncertainty
Editorial analysis: For AI and ML practitioners, unclear copyright rules raise the legal risk and compliance cost of using generative models in production content pipelines. According to The Economic Times, Indian entertainment firms are investing heavily in AI for content creation, but current copyright law, which is tied to human creativity, may not clearly protect AI-assisted or AI-generated works. The Economic Times reports lawyers warn that, without specific legislation or case law, such works face risks of duplication and misuse, complicating licensing, attribution, and monetization for studios and creators. The article highlights that creators and rights holders in India currently have limited legal recourse under existing statutes, per The Economic Times.
'The fate of Earth depends on a delicate balance': Our planet may survive the death of the sun after all, new models hint
When the sun dies, it will become hundreds of times its current size and engulf the innermost planets. Earth may escape this infernal fate, according to state-of-the-art stellar evolution models.
Austria lobbies EU to host Anthropic AI after US curbs, Bloomberg News reports
Austria is pushing the European Union to consider hosting Anthropic AI system within its borders to counter efforts by the U.S. to block foreigners from using the company's most advanced models, Bloomberg News reported on Sunday.
Starz Entertainment (STRZ) Stock Sees Fair Value Lift After Q1 Analyst Target Increases
Price targets for Starz Entertainment have shifted as the analyst fair value estimate moved from US$19.38 to US$28.50, putting a higher reference point in focus for investors tracking the stock. Recent Street research has turned more constructive after the Q1 report, with several firms lifting price targets and updating models to reflect how they now view execution risks and valuation support. In the sections that follow, you will see how to interpret these changing targets and what they...
US close to allowing Anthropic to restore Fable 5 model, Axios reports
The Trump administration is close to allowing Anthropic to restore access to its Fable 5 model, Axios reported on Saturday, citing a source close to the situation.
Satya Nadella said every company should build its own AI model
Satya Nadella said there should be "as many models in the world as firms in the world" and that reliance on a small set of models pose economic risks.
US government allows Anthropic limited release of AI model that sparked cybersecurity concerns
The US government has allowed Anthropic to release its powerful Mythos AI model to select companies and organizations, revising license requirements after ordering an export block earlier this month in the wake of national security fears.
Best Prime Day Tablet Deals From Apple, Samsung and TCL
Tons of Apple and Android models are still on sale, but these holdover bargains are selling out fast.
iPhone 18 Pro and Pro Max May See $200 Price Increase
Apple's iPhone 18 Pro models could be up to $200 more expensive, according to a prediction from analytics firm IDC. IDC expected Apple to raise iPhone 18 prices, but prior to yesterday's Mac and iPad price hike, the prediction was a $100 increase for the 18 Pro and Pro Max, and a $50 increase for the base models. IDC Senior Director of Data & Analytics Nabila Popal says the magnitude of the Mac and iPad price increase points to even higher iPhone 18 prices.
OpenAI launches limited preview of GPT-5.6 at US government's request
OpenAI said they were complying as part of its agreement with the Department of Defense, which allows the department to use its AI models.
Some In Silicon Valley Want To Build A Machine God: Here's What Business Leaders Should Build Instead.
What young people need to become capable, grounded adults is not a faster model release.
2027 iPhone 18 and iPhone 18e to Get 9GB RAM and A20 Chip
The lower-end iPhone 18 models set to launch in spring 2027 will feature 9GB DRAM, up from 8GB, according to Apple analyst Ming-Chi Kuo. Kuo says the A20 chip Apple plans to use for the devices will have 1.5GB x 6 dies for a total of 9GB RAM, instead of 2GB x 4 dies as the current lower-end iPhone 17 models use. By lower-end iPhones, Kuo is likely referencing the iPhone 18 and the iPhone 18e, both of which are rumored to be coming around March or April of 2027.
New iPhone 18 specs report raises big question of iOS 27 limitations
Apple’s base model iPhone 18 might not get as much RAM as expected—raising questions about support for iOS 27’s most demanding features.
MAI-Code-1-Flash for Copilot Business and Copilot Enterprise
MAI-Code-1-Flash, Microsoft AI’s in-house coding model, is now generally available for GitHub Copilot Business and Copilot Enterprise, building on its recent expansion across Copilot surfaces. Purpose-built for coding and optimized…
Apple's OLED 'MacBook Ultra' Will Stick With M5 Pro and M5 Max Chips
Apple's upcoming high-end MacBook model featuring an OLED touchscreen display will use the company's current M5 Pro and M5 Max chips, according to Bloomberg's Mark Gurman. The new, top-of-the-line device will launch "between late this year and early next year," Gurman said, adopting the existing high-end Apple silicon chips rather than next-generation M6 versions.
Apple’s Touch MacBook to Use M5 Pro and Max Chips, With M7 Models to Follow
Apple Inc.’s first-ever touch-screen laptop will rely on the company’s current high-end M5 chips, rather than next-generation silicon, though the company is working on a follow-up model with future M7 processors.
Sweden and WHO launch new long-term initiative to transform Ukraine’s health system
WHO and the Swedish International Development Cooperation Agency (Sida) have launched a new multi-year cooperation project to support the long-term recovery and transformation of Ukraine’s health system. The new project, “Ukraine’s Health System Transformation Initiative: Strengthening Health Governance, Health Financing and Service Delivery for Long-Term Recovery”, was launched at the Ukraine Recovery Conference 2026 in Gdansk, Poland on 26 June, and will run from June 2026 to 2029. Sweden will contribute approximately US$ 26 million (240 million Swedish krona) to support this project. This contribution forms part of Sweden’s broader support to Ukraine through the Team Europe approach, which brings together the European Union, its Member States, and key partners such as the European Commission’s Directorate-General for Enlargement and Eastern Neighbourhood and Enabel, and WHO as lead health agency, to support Ukraine’s recovery, reform agenda and European integration.“Ukraine’s health recovery cannot be measured only by what is rebuilt, but by whether people can count on the health system when they need it most. The scale of the task is immense, with health reconstruction and modernization needs estimated at US$ 19.4 billion over the next decade. Sweden’s US$ 26 million contribution to Ukraine’s Health System Transformation Initiative is a timely investment in the institutions, financing and services that will support Ukraine’s long-term recovery and European integration. WHO remains a trusted partner of the Government of Ukraine in advancing this process. I am deeply grateful to Sweden for its consistent support and partnership,” said Dr Hans Henri P. Kluge, WHO Regional Director for Europe. More than 4 years of war have placed unprecedented pressure on Ukraine’s health system, creating 3 interconnected challenges. The first is responding to the immediate consequences of the war and the urgent health needs of the population. The second is recovering and modernizing health services today. The third is continuing reforms and aligning the health system with European standards in the context of Ukraine’s future accession to the European Union. The war has led to large-scale population displacement, an increasing need for trauma care and rehabilitation, and shortages of health workers. High out-of-pocket payments in Ukraine make access to health services more difficult. Around 46% of total health expenditure is paid directly by individuals, placing a significant financial burden on many households and underscoring the need for reforms in health financing. Older people, persons with disabilities, women, children and veterans continue to face the greatest difficulties in accessing health services. “Ukraine is demonstrating that health system transformation can continue even during war. Ukraine is also continuing to align its health system with European norms and standards. WHO is committed to supporting Ukraine on this journey. We provide technical support, help coordinate partners’ efforts and support the institutional changes needed to strengthen the system. We are grateful to Sweden for its support. Through this partnership, we can help Ukraine build a more resilient, accessible and people-centred health system,” said Dr Jarno Habicht, WHO Representative in Ukraine. About the Health System Transformation InitiativeThe new initiative will support Ukraine through 3 interconnected areas: strengthening governance and coordination of health sector reforms through more inclusive coordination platforms and structured policy dialogue; transforming service delivery by reinforcing a primary health care-centred model that integrates family medicine, nursing and midwifery; and improving financial sustainability by supporting reforms that ensure the long-term viability of the national health system and reduce out-of-pocket payments for households. Overall, these reforms are expected to make the health system more coherent and easier to navigate, improve the quality and continuity of care, and ensure more equitable access to services, particularly for those who need them most. They will also support Ukraine’s progress towards a more modern health system aligned with European standards. “We are convinced that long-term recovery is not possible without strong, high-quality, person-centred health services that are accessible to everyone. Our partnership with WHO is designed to support deep and lasting systemic changes. Investments in human capital especially autonomous midwives, whose role for maternal, newborn and adolescent sexual and reproductive health cannot be understated, stronger governance, digital transformation and the financial sustainability of the health system are investments in Ukraine’s future. We are proud to support this process,” said Malin Perhult, the Head of the Ukraine Unit at Sida. Focus throughout implementation will be given to the most vulnerable population groups, including older people, women and children, and persons with disabilities, who have been affected by the war and face greater health-care needs. The initiative will be implemented in close cooperation with the Ministry of Health of Ukraine, the National Health Service of Ukraine, the Public Health Centre of Ukraine, regional authorities and international partners. This project will help Ukraine move towards a system where everyone can access the health care they need. It will strengthen primary care, make the health finance system more stable and predictable, and reduce the out-of-pocket costs that Ukrainians face when using health services. As a result, the Ukrainian health system will become more aligned with European standards and more sustainable in the long run.
Slotkin says Democratic Party needs 'new leadership': 'Old models are no longer working'
Sen Elissa Slotkin calls for new Democratic Party leadership, saying old models no longer work and the party must simplify its message to win back voters.
Evaluating the robustness and readiness of large frontier models in health AI applications
Nature Medicine - Adversarial evaluation of leading AI models uncovers gaps between benchmark success and robustness, highlighting limitations in current health AI benchmarks and their ability to...
M6 MacBook Pro Expected This Year With Apple's First 2nm Chip
Apple could launch an updated base model 14-inch MacBook Pro with an M6 chip as soon as this year, reports Bloomberg. There could also be M6 chip updates for the Mac mini, iMac, and MacBook Air, but Apple is testing an M6 MacBook Pro. Apple plans to introduce the M6 in late 2026, and for the first time, it will be a standalone chip. Apple is not working on M6 Pro or M6 Max chips, and will hold off on higher-end chip options until the M7 series launches in 2027.
Making Our Own Luck
We are cross-posting a piece that former NIH official Kris Willis wrote for Macroscience. Kris is now the President and Founder of the Woodley Park Institute, for which I’m a board member. Picking winners or hedging bets? Federal science agencies have long wrestled with the question of how to ensure their billions of dollars of grants and contracts result in maximum benefits for Americans. On the surface, it might seem that a goal-oriented, interventionist style of management would be the best policy: prioritize our most pressing problems and distribute funding accordingly.This top-down strategy creates a unique hazard, though: bad choices can send resources in the wrong direction, resulting in slow progress that impedes the delivery of tangible benefits to citizens. Moreover, if decision makers pursue an applied advance when the underlying scientific principles remain poorly understood, they risk costly failures and a loss of support for the research enterprise at large. Examples include Nixon’s 1971 War on Cancer, undertaken on the premise that a cure could be achieved in less than a decade, the drive to build an operational commercial fusion plant by the mid-1990s, and the National Plan to Address Alzheimer’s Disease, which failed to produce the effective treatments and prevention strategies promised by 2025. The contrasting laissez-faire approach is to hedge your bets. If the path to an advance is impossible to predict, then the wisest choice might be to distribute funding to as widely as possible. The main risk of this strategy is that spreading funding thinly may limit the resources available to the most promising research, resulting in the same negative outcomes as the interventionist approach: limited support for the most promising topics, slow progress, and delayed returns. In reality, at science agencies like the National Science Foundation and National Institutes of Health, program managers navigate between these two extremes, setting some funds aside to target high-priority areas and using the rest to cover the widest possible range of meritorious proposals. This middle path seems like the most rational way to proceed, but it still requires making choices. How much should be set aside for high priority topics? What should those topics be? How should we define merit? Expert opinion can provide a helpful guide, but leading experts can have remarkably different opinions about what matters and what should be prioritized. Moreover, experts and administrators alike can be risk averse, giving an edge to high-profile, well-established concepts. What’s really needed is a data-driven framework to help guide decision-making, one that doesn’t simply repackage prestige or incumbency. Recognizing breakthroughs years in advance Many breakthroughs fail to attract funding or recognition at the earliest stages of development. Katalin Karikó, for example, spent years struggling to win grants for work on mRNA that would eventually win her and Drew Weissman a Nobel Prize. Similar stories can be told about Jim Allison’s groundbreaking studies leading to the development of cancer immunotherapy, Stan Pruisner’s demonstration that prions can self-replicate without DNA, or Robin Warren and Barry Marshall’s proof that Helicobacter pylori, not stress, causes ulcers. Yet at some point, the scientific community recognizes and responds to transformative breakthroughs like these. How does that change happen? And what if science funders could identify the areas that are on the cusp of a breakthrough? Those questions led my collaborators and me to study how scientists responded to past breakthroughs. Based on patterns in that data, we developed a means of predicting future breakthroughs, using biomedicine as a proof of concept. It’s worth taking a moment to describe how our approach works. Briefly, our prediction process begins by grouping the 18 million or so peer-reviewed papers in PubMed, the authoritative database of biomedical research, into roughly 50,000 unique topics. A small subset of these topics are so widely acclaimed as breakthroughs that they have been recognized with a major prize like a Nobel or a Lasker Award. We theorized that studying the development of these outliers over time, especially before they gained acclaim, was the key to identifying future instances of them. After defining topics, we chose 21 representative breakthroughs and asked what they looked like before they won prestigious prizes. To answer that question, we re-ran our topic-mapping algorithm repeatedly, winding back the clock one year each time, stringing together the years to follow the progress of each field as it grew and advanced. We found that in each case, the years leading up to a discovery followed a pattern: a burst of papers on a new, rapidly evolving topic, many of which quickly became influential. These characteristics—the percent of papers that are new, the percentage of papers that are brought in from other topics, and the influence of each individual paper—can all be measured separately for any given topic. Together, they act as a predictive signal that is detectable an average of five years before a transformative discovery is made, and up to thirty years before the discovery receives a major prize. Scanning the current research landscape for topics that display this signal allows us to predict what work will likely produce a future breakthrough. Each year we analyzed includes four or five signals, a number that appears to have remained constant across a twenty year time frame. In their classic work on the sociology of science, Bruno Latour and Steve Woolgar established that the desire to participate in a major discovery is an important motivator for scientists as they consider whether they should take up (or abandon) a research problem. Although further work is needed, the simplest explanation for our results is that this behavior is widespread enough to detect at scale. A foundational advance, or something like it, draws the attention of scientists and causes them to change the direction of their research. They vote with their feet, staking their own reputation and careers by publishing on and citing the new idea. That upswell of interest is the foundation of our breakthrough signal. What kind of research does our model identify as a breakthrough? After building a model based on the patterns in our 21 preselected breakthroughs, we tested it by identifying all early signals of discovery from 1994 through 1997. Of the 18 signals we found in that time period, 17 can be traced forward in time to a breakthrough. Examples include super-resolution fluorescence microscopy (see the image above), the directed evolution of proteins and enzymes (Chemistry Nobel, 2018), and sequencing the human genome (National Medal of Science, 2008). The discovery of the role of leptin signaling in obesity is a particularly interesting case study. Around 1950, scientists noticed the existence of a type of lab mouse that suffered from a unique inherited form of obesity. When given the freedom to choose their own diet, these mice ate more than normal and preferred food that was high in fat. Researchers had few clues as to why the animals overate; early experiments pointed to the existence of a soluble ob factor found circulating in the bloodstream that regulated appetite, but its identity was unknown. In 1994, Jeffrey Friedman and colleagues identified and sequenced the ob gene, noting that the protein it encoded appeared to fit the profile of a circulating factor. A year later, a trio of high-profile publications demonstrated that ob was a hormone that regulated body weight and fat deposition by regulating appetite. One of these was co-authored by Friedman, who christened it leptin from the ancient Greek word for thin. Using our model, the data from 1996 make it clear this advance would become a breakthrough. Scientists had flocked to study the biology of the new hormone, generating the flurry of new papers and citations required to produce a signal. One of these demonstrated that serum leptin concentrations reflected the amount of adipose tissue in the human body, providing clinical validation of the earlier mouse studies. Before the identification of leptin, scientists were unable to point to a specific molecule that controlled appetite and adiposity, so that it was impossible to rule out non-physiological causes of obesity; its characterization fundamentally changed our concept of weight gain. In 2010, Friedman and fellow pioneer Douglas Coleman were awarded a Lasker for the discovery. Our work also identifies breakthroughs in clinical practice and behavioral and social sciences, even though these areas are less likely to draw the attention of major prize committees. One example that falls into this category is the introduction of endovascular aneurysm repair, a minimally invasive surgical procedure for the treatment of abdominal aortic aneurysm, a leading cause of death among Americans over the age of 65. Relative to the previous standard of care, it reduces in-hospital mortality by almost four-fold. In 2017, Timothy Chuter received the American College of Surgeons’ prestigious Jacobsen Innovation award for his multiple refinements to the technique. Another under-recognized breakthrough identified by our model is the development of standardized survey instruments to assess the quality of life for HIV+ patients. The antiretroviral cocktails introduced in the mid-1990s reduced AIDS mortality, but treatment came with serious side effects. The new evaluations showed that patients whose disease progressed had worse physical functioning than Americans with other chronic diseases, while those who were asymptomatic maintained a health-related quality of life on par with the overall US population. This evidence made it possible for patients and activists to argue that even in the absence of a total cure, and in spite of the side effects, alleviation of symptoms was a worthwhile priority for clinicians. My colleagues and I have failed to identify any significant recognition for the physicians and health policy experts who pioneered this advance, although in 2016, researchers called for the World Health Organization to set targets for good health-related quality of life as part of its framework to end the AIDS pandemic. From forecasting to funding How should science funders use our predictions? Any serious discussion of what we should do with this new capability needs to begin with an understanding of its limitations. We can’t (and shouldn’t) invest all of our resources in the small number of topics predicted to produce breakthroughs. Innovative new fields are born from existing ones; they rarely arise de novo. If funders don’t maintain a diverse portfolio, the breakthroughs of tomorrow will have no antecedents. Think of this as eating the seed corn, or killing the goose that lays the golden egg. There are also multiple goals of funding beyond basic scientific discovery, including translating discoveries into clinical practice, developing new technologies, supporting economic development, and training new scientists. The investments needed to accomplish these goals are likely different from those required to support emerging breakthroughs. Finally, we must be aware that we may not capture every instance of a breakthrough. The concept is fuzzy, and not every significant discovery is recognized with a major award. Further, breakthroughs are rare, meaning that our dataset is, by necessity, small. This makes formal estimates of accuracy challenging. Although our overall success rate appears to be high, any one signal may turn out to be a false positive. We found one apparent example: the development of the third generation COX-2 inhibitors, Vioxx and Celebrex, which were much celebrated in the early 2000s as effective but non-addictive pain relievers, meets all the algorithmic criteria of a breakthrough. Five years after it received FDA approval, researchers demonstrated that Vioxx was associated with serious cardiovascular complications, and the manufacturer voluntarily pulled the drug from the market. Celebrex remains available, although like other NSAIDs, it carries an FDA warning for increased cardiovascular risk. Decision makers who were overly focused on the breakthrough potential of this research might have wasted substantial resources nurturing an area that ultimately proved to be a failure—but so would those who relied on expert opinion at the time. That said, the potential benefits of funding the next mRNA vaccine or cancer immunotherapy years earlier than we might have are large. When we can’t assume the outcome of an action, it’s worth conducting an experiment. Can targeted support for areas that are poised to produce a breakthrough increase the return on scientific investment without cannibalizing future advances? With the necessary administrative infrastructure in place, conducting this experiment would be straightforward. First, identify all the breakthrough signals between 2018 and 2023, select half at random, and commit to a decade of investment. For biomedicine, a six year window should yield about 30 topics with the potential to produce a breakthrough. Providing strong support to half of these might be accomplished for $300 million a year. That’s roughly half of the recent annual budget of the NIH Common Fund or around 20% of the fiscal year 2025 budget for ARPA-H. After five years, then again at ten, compare to see which group — the one that was actively managed, or the control — produced more breakthroughs, and on what timescale. Although we used biomedicine as an example, the same experiment could just as well be run for physics, materials science, or any other discipline. Any attempt to undertake such an experiment should keep three points top of mind. First, we can predict the topic of future breakthroughs, but the people and vision for how to move the work forward are still important. In practice, this means success requires active program managers with the expertise to develop the science and the authority to do so, including by recruiting investigators. Second, we would be wise to learn from the failures of past attempts to fund transformative research. High among these are funding modestly repackaged work, confusing the genuinely novel with the merely unfamiliar, and relying too much on incumbent investigators. All of these risks can be mitigated by thoroughly and intelligently integrating high quality data into portfolio management. Finally, we need to have patience. Even with strong funding support, producing a breakthrough takes time. If supporting breakthroughs is the best way to nurture the birth of new fields, we also need to accurately describe and properly manage the other two stages, so that we invest wisely throughout the productive lifetime of ideas and divest once they reach the point of diminishing returns. We would benefit from more study of all of these phases, especially the transition from one to another. More research could answer questions like: When does a breakthrough become an established field? How do the availability of funding, the size and characteristics of the available workforce, and the accumulation of evidence that disagrees with prevailing models affect a field’s decline? Exactly how do old ideas give birth to new ones, and can we speed up the process? The more we understand about the dynamics of scientific progress, the better we can maximize the odds that our curiosity leads to results. I’d call that finding a way to make our own luck.
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How should European scientists respond to the US AI kill switch?
Earlier in June, Europe’s worst fears of technological dependence were confirmed when the White House ordered the AI firm Anthropic to stop non-US citizens using its leading models. This kill-switch moment crystalised anxieties in Brussels that the continent, lagging the US on the creation of leading-edge AI models, is now a technological of vassal of Washington. The shock has specific implications for European scientists and universities. Some governments are now worried that with AI being integrated into labs, Donald Trump now has his finger hovering over an off switch for European science. “Having restrictions on this tool, it can have an impact on our own research,” said France’s research minister, Philippe Baptiste, at the VivaTech conference in Paris on June 18.Baptiste, himself a former academic, said that colleagues in mathematics had recently warned him they were now cut off from leading-edge US models, risking their work. “This model is not available anymore now because of the US restriction, and for the first time this had an impact on mathematics,” a field where large language models (LLMs) are making a significant contribution, said Baptiste. So, should European scientists avoid relying on US models in the future? Or would this be a self-harming overreaction? And how is AI being used in science, anyway? What happened?On June 12, it emerged that Washington, citing cybersecurity concerns, had ordered Anthropic to stop non-US citizens using two models: Claude Mythos 5, and Claude Fable 5, a version of Mythos but with guardrails to prevent abuse. Anthropic said Washington’s concerns were overblown. But forced to follow the order, yet with no way to check who was using the models, the company suddenly shut down access for everyone, US citizens included. There’s still no agreement on how to restore broad access. But last week, Bloomberg reported that select US companies, and the US government, still had access to Mythos despite the ban, but the EU’s cybersecurity agency Enisa had been shut out. Class division of researchersIn the longer term, access outside the US should be restored, said Marcel Salathé, co-director of the AI centre at the Federal Polytechnic School of Lausanne (EPFL), because a permanent restriction would be financially ruinous to US AI firms. “Even Trump will eventually budge to economic pressure,” he said.However, US AI firms might end up operating rather like banks, doing due diligence on users of their leading-edge AI models, he went on.European scientists are unlikely to fall foul of such checks, he said. But having a Chinese postgraduate in their lab, or doing a type of research the US disapproved of, could potentially result in access being denied. “It will create a sort of class division of researchers,” he said. More than frontier modelsHowever, successfully deploying AI in science is about far more than just having access to leading LLMs such as Mythos.Instead, many science-specific tools, most famously Alphafold, which predicts protein folding structures, require “far less” computing power to train than frontier models, well within the capabilities of European supercomputers, according to a recent analysis by the Arq Foundation, a Brussel-based AI think tank. Instead, tools such as Alphafold are possible because certain fields, like protein folding, weather prediction or astronomy, have large, clean, standardised datasets that can be used to train predictive models. Rather than compute, “data is the central constraint for AI for science,” the report says. For example, a less powerful physics model trained on CERN’s data “will be more valuable than the best model without certain data,” said Bengüsu Özcan, author of the report. European advantage?Europe could therefore steal a march by using its scientific data and infrastructure to create models US digital giants cannot. “They might actually match or go even beyond what these big [US] companies are doing,” said Özcan.Indeed, some European start-ups hope to create automated testing labs to create the kind of standardised data that could speed up the discovery of new materials. Materials scientists say there’s currently too little data to train models. AI scientistsHowever, even if the bottleneck for AI in science is often data, rather than compute, being at the mercy of the US for LLM access could still become a problem for European scientists. A new class of “AI scientists” based on leading LLMs is also emerging, Özcan’s report says.Unlike domain-specific tools like Alphafold, these try to automate day-to-day scientific work, by providing an overarching tool that coordinates specific models to synthesise existing literature, generate hypotheses or run analysis of data. The problem for Europe, however, is that these tools are sometimes based on US leading models. Google Deepmind’s AI Co-Scientist, for example, is built on Google’s Gemini LLM. Systematic failureThese scientific automation tools are still in their early stages, and still exhibit “systematic failures on scientific tasks,” Özcan’s report says. One of the problems is that the messy, day-to-day process of scientific discovery is largely not documented, meaning LLMs don’t have a good source of data to learn how scientists actually work. Meanwhile, some tasks, such as literature synthesis, don’t typically require access to leading edge models.However, the performance of AI scientific assistants could improve as companies such as Google pour resources into developing them. Rely on US“Unfortunately, for scientific assistants, there is not much we can do right now except rely on US frontier AI,” said Antoine Bosselut, a natural language processing expert based at EPFL. Chinese-built open models, which can run on local computers, lessening the risk of a shutdown, are touted as one alternative to US dependence. There’s also Mistral, once seen as Europe’s main AI hope, but the Paris-based company has seen its recent models fall behind in performance. But the Chinese alternatives are generally not as capable as US frontier AI models, said Bosselut, unless paired with fiddly, custom tools that allows them to act as independent agents. “Most scientists do not have the time,” he said. Don’t jump ship yetAlthough the kill switch moment is seen a warning shot for European scientists, it doesn’t mean labs should abandon US AI tools immediately. “I do not think the right response is simply to abandon US-based models and systems under the banner of sovereignty or independence,” said Mattias Björnmalm, secretary general of the Cesaer university association. “That would be an overreaction.”Related articlesEuropean sovereignty in AI requires ‘ugly trade-offs,’ say experts Robotic lab start-up makes case for €500M EU-funded materials testing facilityAI in science: is it useful? Instead, European researchers need to ask themselves whether they’re becoming dependent on technology that could be turned off in Washington, said Özcan. “They might not see this today, but they should really start asking this question,” she said. European researchers need a plan B, said Salathé. “I would recommend to every researcher, very proactively explore alternatives.”Own toolsIn addition, Björnmalm and others want European research institutions to develop their own scientific AI tools.Instead of signing AI deals with US digital giants, European universities should be using this money to create their own models, which may end up being superior for research, said Sabine Leonelli, an expert on the use of AI in science at the Technical University of Munich. “Universities in Europe seem to be happy to sign commercial contracts with US companies on the assumption [their AI tools] are better,” she said. But US frontier LLMs are typically opaque, and have been developed without independent scientific input, she said. “This is not good enough for science.”Last year, Swiss researchers released Apertus, an LLM designed to be completely transparent, from its development methods to its training data. The idea is that this makes scientific tools built on top of the model far more reproducible than with closed, commercial alternatives.“Europe needs more of this: serious capacity-building that gives researchers, universities and companies credible options,” said Björnmalm.
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