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Valve Confirms You Can Build Your Own Steam Machine
Support for NVIDIA hardware is also on the way.
Valve admits Steam Machine is "more expensive" than it hoped
The PC giant is non-commital on whether the console's price will come down in the future if hardware costs reduce
The Steam Machine's Companion Cube case is big, expensive, and based on a 19-year-old joke, so I hate how well-made it is
The Steam Machine provides a chance to get reacquainted with the Companion Cube, courtesy of Dbrand's pricey (though admittedly finely designed) case.
Steam Machine is 'more expensive' than even Valve wanted it to be
The PC gaming giant knows some fans won't be able to afford its new system, but Valve didn't want things to work out this way
Pre-RAMpocalypse Steam Machine Pricing was ~30% Cheaper
It's no secret that Valve's Steam Machine is launching at possibly the worst moment for both PC and console gaming hardware, given the ongoing DRAM crisis, but Valve engineer, Pierre-Loup Griffais, has recently shed light on the pre-RAM crisis pricing of the Steam Machine, revealing that it was neve...
Vending machine with risk reduction and healthcare products installed in Linn
A vending machine containing overdose prevention supplies and personal health and hygiene products has been installed in Linn.
AI’s money machine faces first real test in Manhattan primary
Industry spends millions to target candidate who supports greater regulation of the technology
Valve Explains Why You Have To Pay $1,050 To $1,430 For A Steam Machine
Valve has finally revealed the price of the Steam Machine, and it's more than almost anyone predicted. Can you afford it?
"This is going to be a niche device" – Analysts react to the $1,000+ Steam Machine price reveal
Mat Piscatella, Joost van Dreunen, Manu Rosier, and Piers Harding-Rolls offer their thoughts on the price implications for Project Helix and PS6
Valve's Steam Machine ships June 29 for $1,049, but you probably won't be able to buy one yet
Valve says it's using a randomized purchase queue to make the experience "less frustrating and more fair."
Valve: FSR 4 Is Coming to Steam Machine
A huge confirmation that should see significant quality improvements.
Here’s how you can reserve a Steam Machine
Valve’s reservation process is complicated, but fair.
Valve will finally let you build your own Steam Machine with SteamOS for desktop
Valve’s working on official Nvidia support in SteamOS.
Dbrand launches Companion Cube enclosure for Steam Machine, "Poverty Cube" option costs $99.95
The cube now gets another cube. Dbrand has opened preorders for its Companion Cube enclosure for Valve’s upcoming Steam Machine.
Dbrand Is Now Taking Orders for Its Steam Machine Companion Cube Case
Dbrand is now officially selling its Portal-themed Companion Cube case for Valve's yet unreleased Steam Machine.
Steam Machine Companion Cube now up for pre order, arrives next month with matching Steam Controller skin
First teased soon after Valve announced the Steam Machine, dbrand's Companion Cube case is now available to pre-order from $99.95.
AMD has reportedly released FSR 4 for RDNA3 GPUs in Valve Proton Experimental
AMD FSR4 appears to be coming to Valve’s Proton Experimental.
Here’s who’ll win the World Cup, according to science
Statisticians from across Europe teamed up to train a competition-predicting, machine learning algorithm. This is what they found.
AI Startup Midjourney Pivots to Health With Ultrasound Machine
AI startup Midjourney Inc. announced its first hardware project at an event in San Francisco, outlining an unexpected move into the personal health and medical industries.
Researchers discover 500 hidden earthquakes beneath Antarctica: 'Improve our understanding of possible futures'
“As machine-learning tools continue to improve, they could reveal that deep, continental-interior earthquakes are more common than currently recognized.”
Valve Steam Machine Benchmarks Show Near Twice The Uplift Over Steam Deck & Comparable To Ryzen 5 5600X at 30W
New benchmarks of Valve's Steam Machine show performance comparable to a 6-core AMD Ryzen CPU from 2020, but could be decent if priced right.
Scientists stunned by the world’s largest whale “graveyard” millions of years old - Futura-Sciences
The Hidden Depths of the Diamantina Zone Deep beneath the Indian Ocean, researchers from China, Italy, and New Zealand got more than they bargained for during their recent expedition. Exploring the remote Diamantina Fracture Zone—which formed during the separation of Australia and Antarctica—the team operated the Fendouzhe submersible, a machine...
Team's post-op kidney injury risk model could aid prevention
The machine learning-derived model was 88% accurate in ranking preoperative patients according to risk for postoperative acute kidney injury.
Trump wins two, loses one: Georgia billionaire delivers rare blow to endorsement machine
Trump-backed candidates won two of three key GOP runoffs in Georgia and Alabama, but lost the gubernatorial race to billionaire Rick Jackson.
Steam Machine Performance Benchmark Leak Signals Approaching Launch
Since the news broke that the Valve Steam Machine would be delayed, there have been countless conversations online about how the Steam Machine would be dead on arrival because of its expected pricing and aging internals—a six-core Zen 4 CPU and a Radeon Navi 33 GPU with 8 GB of VRAM—but a recent set...
Skill game ruling leaves Pennsylvania businesses facing possible taxes, new regulations
A Pennsylvania Supreme Court ruling that classifies skill games as gambling devices is raising concerns among small businesses that rely on the machines for extra revenue.
AI and brain-computer interface allow speechless ALS patient to work a full-time job
The hardware isn't new, but a UC Davis research team's machine learning-powered method of translating brain activity in an ALS patient into sentences with 92% accuracy is
Steam Machine one step closer to launch as benchmarks surface online, here’s how it compares to the Steam Deck
We can now have an early look at some Steam Machine benchmarks after results were uploaded to Geekbench, suggesting reviews are underway.
NASA Uses Machine Learning to Enhance Flash Flood Warnings
The Transient Artifact and Continuous Learning System (TACLS) leverages data from continuously operating satellite networks coupled with machine learning models to help meteorologists at the National Weather Service forecast flash floods more efficiently.
The Steam Machine Is Likely in Testers’ Hands, as 2 Fresh SteamOS Benchmarks Leak
Steam Machine "Fremont" hits Geekbench running SteamOS, hinting at an imminent Summer launch for Valve's new console
Steam Machine could launch as early as this month, leak claims
After Valve posted a hopeful, yet vague, update on its exciting new console, new leaks point to an official Steam...
Steam Machine reviews may be underway as two new Geekbench listings surface
Valve's Steam Machine was once again spotted on Geekbench with two separate listings, suggesting that reviews may be underway.
Geoffrey Hinton
The machine-learning guru discusses how politics is undermining U.S. science
Chicago City Council to vote on sweepstakes machine ban as bar owners warn of business closures
Chicago alders are divided over a debate on whether to ban or keep sweepstakes machines legal in the city.
Oprah Winfrey blesses new CT scanner she helped fund in Hawaii
Maui Memorial Medical Center, a 214-bed acute care hospital in Wailuku, celebrated the new computed tomography machine with its imaging team on June 8.
Writing science that humans and machines can read
Large language models are now routinely used to search, summarize and synthesize the literature at scales impossible for any individual researcher—yet scientific publishing has not adapted to that reality.
68 quadrillion underground miles of fungi
With machine learning and a high-resolution imaging robot, scientists measured and mapped the extent of Earth’s carbon circulatory system.
SUN Bucks, MRI machines and more. Here's the latest Louisiana health news.
Health Notes is an occasional listing of health happenings around Louisiana. Have something you'd like to share? Contact us at margaret.delaney@theadvocate.com.
Steam machine reportedly sent to reviewers as embargo date and package contents leak
According to a new leak, the first Steam Machine review units may already have been shipped to reviewers and content creators. The rumored review embargo date and possible package contents have also surfaced.
Valve just imported 13 tons of VR headsets in one day
And probably 141 tons of Steam Machines in the past 50 days.
Latest News In AI Chips - AI-Powered Shift: Transforming Data Into Business Intelligence
Treasure Global Inc. has secured a US$15 million contract to develop an AI-powered Social Listening Platform for Creative World Industries, emphasizing the growing demand for AI systems that convert digital data into actionable insights. This platform leverages machine learning and NVIDIA-powered infrastructure to provide real-time sentiment and trend analytics across various sectors. The deployment underscores a trend in the AI chips industry towards enhancing real-time decision intelligence...
Scientists Measure Earth’s Vast Underground Fungal Webs
With machine learning and a high-resolution imaging robot, scientists measured and mapped the extent of Earth’s carbon circulatory system.
Time for an AI checkup: Flaw found in machine learning for sepsis treatment
Shengpu Tang, Emory assistant professor of computer science, found a flaw in many peer-reviewed studies using the AI method known as reinforcement learning as a theoretical guide for the treatment of sepsis.
Dwayne Johnson on Cancer Scare, Not Talking Politics and Oscar Snub
Dwayne Johnson admits he wishes he got an Oscar nomination for 'The Smashing Machine' and reveals a recent cancer scare.
Bypass Siri AI Waitlist on macOS 27 Golden Gate Beta: Here's How
If you installed the macOS 27 Golden Gate developer beta and have signed up to the Siri AI waitlist but are still waiting to be accepted, there's a Terminal command workaround that enables the new virtual assistant on your Mac immediately. If you're still reading, since you're on the first macOS 27 developer beta, we're assuming you are running it on a test machine, and not on your primary Mac. We're also assuming you're comfortable with using the Terminal app.
Family business grows from one man, one machine to major name in packaging industry
They moved from Minnesota to South Dakota, saw a manufacturing market opportunity -- and evolved into a national leader in their industry.
‘Smart’ public health vending machine expands access to free health resources in York County
Leaders from Penn State College of Medicine, WellSpan Health, York County and local community organizations gathered to celebrate the launch of an interactive public health vending machine.
We can create the future of science right now
Paul Litvak is the founder and Executive Director of the Robyn Dawes Institute and a Visiting Scholar at UC Berkeley. He has a PhD in Behavioral Decision Research from Carnegie Mellon where he studied emotions and the sunk cost bias. Over 15 years in industry, he solved a wide range of challenging technical problems. At Meta he created models optimizing the ad review process. At Google he ran experiments to measure social influence. At Airbnb, he was a product manager leading machine learning teams optimizing search ranking and price suggestions. He also co-founded and led product at Rhythmic Health, a venture-backed biosensing startup, creating an accurate low cost system using a color changing strip and a smart phone to measure salivary lactate. The bottleneck At this point, it is uncontroversial to say that science needs to stop using the PDF article as the unit of knowledge and currency. The unbearable slowness of scientific publishing, the profit motive and margins: I’m not saying anything new. The PDF also sucks because it’s hard to extract structured information, which makes it hard to do evidence synthesis. As a result, we do much less evidence synthesis than is needed. And evidence synthesis ultimately undergirds most policy and medical decision-making. I can see second-by-second real-time odds for any sporting or newsworthy event, but a school board can’t see the best evidence on whether their 8th graders should be taught algebra. As a society, we don’t treat this as an important problem. Again, not controversial. Not only is the problem well understood, but the solution has already been laid out. What we need is AI-assisted living evidence synthesis - (1) an open knowledge graph of atomic claims, (2) claims linked to evidence, (3) assessment and synthesis of each piece of evidence, and (4) continuous updating with new data. What few realize (yet) is that the technical capacity to build this vision for a significant portion of science already exists. Not only that, scientists and startup teams are already building many of these components. I know this because I’ve been surveying the space and talking to many of the builders. There are some missing pieces: for example, evaluations of how well some of the components work. But at this point, most of what’s missing is a fully end-to-end working integration of all of these parts. In the rest of this essay, I’m going to lay out all the parts of a working living evidence layer for science and who is working on them, and propose concrete next steps for building this system. What’s now possible The diagram above outlines the components of a living evidence synthesis platform, including some of the teams working on each component1. Scientific PDFs are processed into claims with associated evidence. The evidence is subjected to a forensic audit, methodological evaluation and robustness and reproducibility checks. Finally it’s given a weight in a continuously updating synthesis. What follows is a description and status of each component and a few of the teams working on them. Document understanding The first thing you need to be able to do is turn an article into structured data. Mostly that means parsing PDFs. There are often multicolumn layouts that confuse non-specialized PDF to text processing libraries. For scientific papers, there is the added complexity of parsing formulas and tables and figures. This is a really hot area - there are startups offering APIs, and it seems like a new open source package gets posted to Github every few weeks. What follows isn’t exhaustive. A package called GROBID was the state of the art for a while, they didn’t update their package for nearly two years until very recently. In the meantime reducto.ai released an AI powered PDF extraction API, PaddleOCR became popular, IBM released a model called Docling, and both Mistral and Gemini created models and libraries. I also know of at least one other well-funded psychology research group working on a paper parser. By contrast, there are few open evals in this space, with no extensive evals for complex table comprehension in particular. Nonetheless, I’m confident this will be a solved problem soon, given the combination of LLM advances and developer interest. Hypothesis level extraction There has been increasing interest in comprehending the extracted text of papers and linking information to evidence for each hypothesis. A lot of work has already been done. Trialstreamer (Marshall et al. 2020) and RobotReviewer LIVE (Marshall et al. 2023) demonstrated automated extraction of trial population, intervention, and outcome at scale on clinical RCTs. PaperQA2 (Skarlinski et al. 2024) and Ai2 ScholarQA (2024) extended this to retrieval-augmented question answering with citation grounding. Elicit, Consensus, and SciSpace operationalized claim-level extraction for end users. OpenEval (Booeshaghi et al. 2026) is the most recent and most ambitious: 1.96 million atomic claims extracted from 16,087 eLife manuscripts using Claude Sonnet 4.5, grouped into ~299,000 results, with LLM evaluations showing 81% agreement with human peer review on a 2,487-paper subset. None of these solutions link claims to test-statistics, as you would need to evaluate randomized controlled trials. This is why I built the evidence.guide API - to extract hypotheses and associated test statistics from behavioral science papers. The best public eval of this kind of extraction I’m aware of comes from the recent SCORE project - they had humans code thousands of psychology papers to extract their claims by hand. It would be extremely helpful to the world if all scientific PDFs were available as structured open data. I’ve been working to make this happen, both directly at Berkeley and through coordination with large entities I can’t yet speak of; as hard as it is to do, I think it’s possible2. Forensic audit A lot of work has been done on forensic audit, but some gaps remain. Of course, for biology papers that rely on images for evidence, there are a variety of tools (notably Proofig and ImageTwin) to spot anomalies. These are still well short of what sleuths like Elizabeth Bik can do on her own, but these tools are constant companions among fraud analysts. There’s someone working on auditing Excel files for anomalies, and a number of teams are automating numerical checks like GRIM and SPRITE, including Scrutiny project, the INSPECT-SR team as well as statcheck. The regcheck team is building a way to use AI to compare preregistrations to analyses in papers, to ensure there aren’t significant deviations. Nonetheless, there are many other kinds of anomalies to screen for, both public and less publicly known. And there are no formal evals for anomaly detection that I’m aware of. Still, there’s a lot to draw from in this space and I’m pretty certain we will be able to scan papers for most kinds of obvious anomalies in the near future. Methodological review This area has been white hot, though I fear for many of the startups in this space, because this capability may become commoditized. There are at least six different AI peer review companies, including Refine.ink, Reviewer3, ReviewerZero.ai, Q.E.D. Science, Paper Wizard, and Isitcredible. Coarse (a pun on refine) was also recently created as an open source alternative. These systems provide qualitative feedback on the content of papers, spotting methodological weaknesses and mathematical errors. They seem to work pretty well, and many academics report bitterly that they exceed the average quality of typical peer reviewers. But there are few evals here either. What evals exist so far involve using LLM-as-judge (circularity problems abound) or comparing against human reviews of questionable quality. What you’d ideally want is an eval that measures capturing known errors in papers3. Reproducibility and robustness Another active area has been using AI agents to automate computational reproducibility4 and robustness5 checks in papers that report numerical results. For more recent papers where data and code are available, AI agents can see whether they can re-run the analyses and produce the numbers reported in the published paper. In addition to a handful of individual academics who have been experimenting using Claude Code for this, the Institute for Replication is a leading group working on building an end to end system. The evals related to this problem are the most mature, with CORE-Bench (Siegel, Kapoor, Narayanan 2024) and PaperBench (OpenAI 2025) available to benchmark agents on this task. There is also work on getting AI agents to test alternative ways of analyzing the data to ensure the results are robust to small analytic design choices. Synthesis This is the most underdeveloped area where significant investment is required. Although some automated evidence synthesis systems exist — for example, otto-sr is building an AI agent to write systematic reviews — none of these incorporate the full range of paper level signals to weight evidence appropriately. Nor is there anything like an eval or a gold standard for a good systematic review. Arguably Cochrane reviews are the closest we have to gold standard human systematic reviews, though I’ve heard academics in the know complain about their uneven quality. A key question for a synthesis platform is how to weight anomalies and methodological issues in assessing the quality of a piece of evidence. This is an unsolved problem and one I’m very keen to work on. Continuous updating There are many pieces of basic infrastructure available for monitoring for new research and initiating updates. OpenAlex is the current open citation graph. Retraction Watch integrated into Crossref in October 2023. Scite tracks how citations support, contrast, or mention prior claims. The Living Evidence Network demonstrated continuous-update workflows in clinical guidelines. Engineering this is a relatively straightforward task. When you look over this technical architecture and all the progress being made, it’s hard not to be optimistic that a living guide to scientific evidence will be built. The stakeholders are ready The social infrastructure for this is starting to coalesce — it’s not just a pie in the sky academic exercise to imagine this coming into existence. Institutions like the Center for Open Science, the Institute for Replication, the INSPECT-SR, the Living Evidence Network and more are all working on scaling work to improve research quality. Funders are also aligned. The Sloan Foundation has funded living evidence work through COS. Coefficient Giving supports the Institute for Replication and COS. The Astera Institute and the Institute for Progress have shown interest in this space. NIH has established an Office for Replication and Reproducibility. Although there are (very unfortunately) serious headwinds in science funding generally, there is an active group of funders interested in metascience. A brief word about what I’ve been doing at RDI. First, as a Visiting Scholar at Berkeley I’ve been actively figuring out how a non-profit and a public university can conduct and make public the results of large-scale academic article data mining. With some of the money I raised from donors, I commissioned a legal analysis of recent case law and publisher text data mining (TDM) agreements in order to understand whether a massive open data mining of academic articles is possible (with caveats, it is). I’ve also been working to bring together stakeholders in this space, and identify gaps. I’ve also been doing some software development in this space, with more to come. A pilot proposal The assumption undergirding all of this is that an AI, given all this information, would make the right judgment about a scientific claim with lots of conflicting evidence, weighing all the factors appropriately. That’s the hypothesis we need to test. Randomized control trial research is the best place to focus on first. RCTs are used to make many of the important decisions in society - from medical trials to public policy changes. And they use a relatively uniform set of inferential statistics with lots of known and available diagnostics. Behavioral science experiments, within the broader realm of RCTs, should be first used as a testbed whose results can be generalized. Because behavioral science is at the vanguard of open science practices, replications abound (there are thousands of them) to serve as ground truth training data. Key Hypothesis Therefore the pilot would test, in behavioral RCTs that have been replicated, whether the quality of evidence for a claim can be used to accurately predict whether that claim will replicate. Secondary Hypotheses Compared to claims that replicated, non-replicated claims demonstrate a greater share of forensic anomalies in their source literatures. Hypothesis level claim and statistic extraction is accurate enough to scale living evidence without onerous human review costs. Replication prediction is more accurate than prediction markets6 or journal prestige. If all the different quality signals we gather do accurately predict which studies will replicate, then we can use that model to score evidence to power the living evidence layer. Why this is informative regardless of outcome If the pilot succeeds, the architecture extends to medical RCTs (where Living Evidence already operates and integration is mostly about claim representation), then to slices of basic biology with stable replication structure. If it fails, the field learns which quality signals are load-bearing and which ones metascience has oversold. Either result is a contribution to knowing what the literature supports. Implications for funders Because this burgeoning ecosystem of builders already exists, a well-informed philanthropic or government funder could play a crucial catalyzing role in bringing this future about. They could play at least three roles: creating open structured datasets, publishing open benchmarks and incentivizing the solving of key technical challenges. First, open archives of papers that the government maintains, like PubMed, could be turned into structured data amenable to large scale metascience and claim aggregation. I know the US government already has an interest in doing this, though some key open questions remain unanswered. How do you determine the best models and systems for accurately extracting information from papers? How can you establish a robust way to allow researchers to flag errors and correct them? And finally, how do you create a legal regime in working with publishers to maximize the scope of available papers? For the latter, a university or a private philanthropy may be better positioned to make structured data publicly available under journal subscription terms or fair use. Philanthropists or government funders could also coordinate to create or commission benchmarks that evaluate whether important problems have been solved. For example, an open benchmark for claim extraction from a range of different scientific article types would be extremely helpful. Ensuring the underlying data are accurate is vital for creating these evaluations. I’ve discussed opportunistically using various human-created datasets for this purpose, but a consistent problem is that errors in human data make it difficult for them to serve as a gold standard. Finally, with structured data and benchmarks available, the government or private philanthropy could use them to incentivize groups to develop machine learning systems that meet these benchmarks. Prizes are one potentially valuable tool for this. For example, you could establish a prize for a system that accurately updates a living meta-analysis for a small set of claims. Prizes are particularly useful as signals of problem importance, and can help create vibrant ecosystems of public and private research—see, for example the role the government played in kickstarting the current work on nuclear fusion. Conclusion The drawbacks of the current scientific publishing system are known. Scientists agree, metascientists agree, philanthropists agree: the published PDF plus citation graph isn’t the right substrate for maintaining a representation of the evidence base in science. The pieces needed to build the alternative either already exist or are rapidly taking shape. The community is forming around exactly this problem, with concrete partnerships and shared infrastructure. A pilot should start on behavioral science RCTs because that’s the slice of empirical science most amenable to legibility, where replication ground truth is richest, and where the failure modes are best documented. What’s been missing is the galvanizing mission to assemble these pieces into something that works. That’s what I’m proposing to build. *** 1 I have a broader field map that I’ll release publicly soon. This is me, building in public! 2 If this is something that you are excited about, please reach out and talk to me. 3 More on this very soon too! 4 This tests whether, given the code and the data, you can get the same statistics as reported in the published paper. 5 This tests whether the results are the same as a paper’s given alternative analytical decisions in conducting the analysis (like outlier omission). Closely related is the idea of a “multiverse” where you come up with many different ways of answering the same underlying research question with the same data, and test whether the results hold in all those alternative methods. There’s been work on the latter as well. 6 Some of the replications, e.g. those from the SCORE project, had paired the experiments with forecasts from prediction markets. So we get to look at this for free.
The weather and climate science AI revolution isn’t revolutionary
Machine learning has its limits—how is it being used?
Classic race planned in place of excluded sidecars
The Southern 100 Club says it plans to allow classic machines to race instead of modern sidecars.
My 10-year-old started a vending machine business
Christina Nicholson says her son Landon launched a vending machine business at 10 and quickly learned lessons about profit and patience.
Steam Machine summer launch confirmed in hopeful update, but still no price
The Steam Machine and Steam Frame have been hit by rising component costs even before launch, but Steam still seems...
Here’s an early look at the Steam Frame Welcome Tour after Valve officially announces summer release window
Valve's Steam Frame is arriving this summer alongside the Steam Machine. Users have managed to get an early glimpse of its setup procedure.
Scientists are seriously asking if bees and ChatGPT are conscious
New studies suggest consciousness can't be judged solely by behavior, whether it's a chatbot discussing philosophy or a bee searching for nectar. Researchers are increasingly focusing on the internal mechanisms of brains and computers, concluding that today's AI is likely not conscious while leaving open the possibility for both conscious insects and future machines.
Valve Confirms Steam Machine Will Ship This Summer
The company also confirmed that its standalone VR headset will arrive in that same timeframe
Is an Online Master’s Degree in AI a Good Idea?
A look at the real-world value of online graduate AI programs, combining hard data with firsthand experience of a big tech machine learning engineer
Pulte Pick Shows How Trump Is Consolidating Power
Plus, the president’s candidate is defeated in Iowa, and inside Trump’s takeover of the American regulatory machine.
The 7 AI Agent Guardrails Every Business Needs Before Things Go Wrong
AI agents promise to automate work, make decisions and transform business operations, but giving machines more autonomy also creates new risks.
Recent mock draft links Rockets to shot-blocking machine
A recent mock draft completed by Jonathan Wasserman has the Houston Rockets selecting Ugonna Onyenso with the No. 39 overall pick.
Where Forensic Science Meets AI: eSleuth, Inc. Names Former ATF Director Ken Melson to Its Advisory Board
eSleuth, Inc., the AI-driven investigative platform putting the power of advanced data analysis and machine learning directly in the hands of investigators, today announced the appointment of Kenneth E. Melson, former Acting Director of the Bureau of Alcohol, Tobacco, Firearms and Explosives, to its Advisory Board. Melson brings a rare depth of expertise spanning federal prosecution, agency leadership, and forensic science policy that directly strengthens eSleuth AI's mission to transform how la
What’s new on Prime Video in June 2026, including ‘The Legend of Vox Machina' Season 4, WNBA games, and more
Plus, check out Pride Month titles already available on Prime Video like 'Overcompensating' and 'Red, White & Royal Blue.'
Ghost in the Machine review – entertaining AI polemic dives into its dark history in race politics and eugenics
The roots of AI in rightwing ideology is examined in Valerie Veatch’s enjoyable doc, including an array of colourful, often crazed, figures
Four researchers win data harmonization competition
The U.S. National Science Foundation National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS) at Penn State has awarded four researchers from across the world for their efforts in a competition to build machine learning-based approaches for streamlining publicly available datasets for reuse.
Willard’s ‘small ball’ tactics a recipe for success
WILLARD–The Willard baseball program has been a winning machine, under Head Coach, Scott McGee. The Tigers will play in their 7th State Semifinal, in McGee’s 19th and final season, Friday night. The bulk of their success, offensively, has come from a method that is “outdated” by today’s standards — ‘small ball.’ Rather than adapt to […]
AI is devoid of meaning and humanity. That’s why its vapid voice suits this political moment
For ease and speed, we are degrading our ability to connect and to organise our societies. We must assert our trust in humans over machines, says Guardian columnist Nesrine Malik
SMU's president has rightly embraced political neutrality
Too many U.S. colleges became political machines. SMU is making space for real debate and the exploration of tough ideas.
Steam Machine launch appears near as Valve adds Welcome Tour to Steam backend
Valve recently added the Steam Machine's Welcome Tour to Steam's backend through a recent update, which suggests the company is finally geting ready to launch the device.
Scientists got mouse eyes to perform photosynthesis — and no, they didn't turn green
Special eye drops containing photosynthetic machinery from spinach leaves have helped combat dry eye, a new mouse experiment reveals.
"This market is not behaving normally" - analysts react to Valve's Steam Deck price increases, and what it means for the cost of the upcoming Steam Machine
Video games analysts chat with Eurogamer about the recent price increase for the Steam Deck, and what this means for Steam Machine.
Key Chemistry Question Answered, No Quantum Computer Required
Do we need quantum computers to fully understand complex chemical reactions? A new result, decades in the making, shows the surprising power of ordinary “classical” machines.
Cultivating Data-Driven Approaches with Plant Science
Launched this winter, the Data-Driven Plant Science course bridges experimental biology with embedded sensing, bioinformatics, and machine learning.
Protein traffic jams may explain aging, memory loss, and Alzheimer’s
Scientists at Stanford may have uncovered a hidden reason our brains decline with age. Studying the ultra-short-lived turquoise killifish, researchers discovered that the cellular machinery responsible for building proteins begins to jam and malfunction over time. Tiny structures called ribosomes start colliding and stalling while reading genetic instructions, triggering a chain reaction that leads to faulty proteins and harmful clumps linked to diseases like Alzheimer’s.
Call Of Duty Warzone Is Shutting Down On PS4 And Xbox One
The popular battle royale will no longer be playable on the older machines later this year
Steam Deck's Massive Price Hike May Not Bode Well for Steam Frame
Valve announced that Steam Deck is getting a sizable price hike, bringing an increase of $240 to $300 to its handheld gaming PC–not exactly a vote of confidence for those of us waiting for Steam Frame, its upcoming standalone VR headset. The company revealed the 512 GB OLED Steam Deck has increased from $549 to […]
Exclusive | The Trump Administration Is in Talks to Fund U.S. Drone Companies
Neros and Donald Trump Jr.-linked Unusual Machines are among the companies in deal talks.
Exclusive | The Trump Administration Is in Talks to Fund U.S. Drone Companies
Neros and Donald Trump Jr.-linked Unusual Machines are among the companies in deal talks.
You can print, slice, and engrave using this desktop crafting machine
Get your Etsy sticker shop off the ground with this single machine.
ASUS ROG Zephyrus Duo review: Outrageously expensive, totally awesome
The ASUS ROG Zephyrus Duo is a gamer’s dream machine, but its price is a nightmare.
Nanoparticles genetically modify several human cell types
In a demonstration that helps pave the way for gene therapies with fewer side effects, several human cell types were genetically modified with protein nanoparticles designed at University of Michigan Engineering and Michigan Medicine.
Loyola’s Data Science in Everyday Life
Loyola University Maryland will hold “Data Science in Everyday Life: Applicability, AI, and Other Trends,” a networking and panel event exploring data science from a range of perspectives across industry and government.A keynote address delivered by data science industry expert David Norton, MBA ’95, will begin the event. Norton is the chairman and chief marketing officer of GALE Partners, a digital and analytics-based branding agency. He was named Chief Marketing Officer of the Year in 2010 and wrote “The High Roller Experience,” a book about data-driven marketing.Norton will moderate the panel discussion, which includes:• Elise Beisecker, senior data scientist in the U.S. Government Accountability Office• Amanda Muller, Ph.D., chief of responsible technology at Northrop Grumman• Franklin Hernandez, MBA ’13, M.S. ’20, senior lead machine learning engineer at Booz Allen Hamilton• Joseph Girsch, M.S. ’21, machine learning analyst at The Johns Hopkins University Applied Physics Laboratory• Mark Wicks, retired vice president of data science, data scientist, machine learning engineer and software developerHernandez and Girsch each earned an M.S. in Data Science from Loyola.The event is free and open to the public. Networking and appetizers will begin at 5:30 p.m. followed by the keynote address and panel discussion at 6:30 p.m. and audience questions and closing remarks at 7:30 p.m. To learn more and register to attend or stream the event online, visit the event webpage.
Jim Cramer Reveals Why International Business Machines (IBM) Should Be Doing Better
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Bond breakout? Big effects of bad data. Immigration and thermostatic politics & dad-chat is coming for dad-books.
Thank you for opening your Chartbook email. Anna Airy, A Shell Forge at a National Projectile Factory, Hackney Marshes, London, 1918 Bond breakout - John Authers Across the developed markets, bond markets are staging a slow-motion car wreck. Looking at the drastic moves in the US, Japan, the UK and France, Barclays’ Ajay Rajadhyaksha commented: “Last week, long bonds broke. Not in one country. In all of them. Simultaneously. Four countries. Four different political systems. Four different central banks. But the same trade — “get me out of duration!”” Each country has its own contributing political problems, but the uniformity of the shift out of long-term bonds with high duration makes clear that something broader is afoot. For Rajadhyaksha, it is “simple and uncomfortable.” The developed world “has too much debt, too little fiscal discipline, and no political appetite for fixing either.” If there’s a trigger, it has been the Iran war and the resulting shock to oil supply. Source: Bloomberg G7 countries are now borrowing at rates that were enjoyed by EM in the early 2020s For contributing subscribers only. Subscribe Trade between China and Russia has grown in recent years For contributing subscribers only. Subscribe Big effects of bad data A decade ago nearly nine in ten Americans, when approached, agreed to fill out the Current Population Survey, which is administered to about 60,000 households each month and asks about, among other things, employment. Fewer than seven in ten do so now (see chart 1). For the Consumer Expenditure Survey, which tries to capture 3,700 households monthly, the response rate is down from 68% to 40%. … When the information becomes less reliable, investment decisions get more difficult to make. Some may be delayed, creating a potential drag on the economy. A new working paper by Nicholas Bloom of Stanford University, Erica Groshen, former head of the Bureau of Labour Statistics (BLS) now at Cornell University, and Duncan Hobbs and Michael Strain of the American Enterprise Institute, a think-tank, hazards an estimate. Preserving trust in “the integrity and quality of official statistics”, the authors claim, generates economic benefits of about $25 for every $1 spent on the BLS, the agency with an annual budget of $700m that is responsible for many of these data. To arrive at their conclusion the quartet analysed an ignoble episode in the BLS’s recent history. On August 1st 2025 Donald Trump sacked Erika McEntarfer, appointed as the agency’s commissioner by his predecessor, Joe Biden. The president alleged, without evidence, that the BLS’s steep downward revision to recent jobs numbers had been “RIGGED in order to make the Republicans, and ME, look bad”. In fact, it was the wanton dismissal that looked bad in the eyes of many observers. In the following seven days there was a 50% leap, relative to the week before, in the average value of the index of Economic Policy Uncertainty (EPU), which tracks the number of articles mentioning such uncertainty that are published daily in American newspapers. This was a discernible jump even when compared to the chaos caused by Mr Trump’s trade war in April 2025 and his real one in Iran in the past two months (see chart 2). Based on Mr Bloom’s earlier study with other colleagues of the EPU’s impact on business investment, industrial production and employment, the authors estimate that the jump reduced American GDP by over $100bn (0.3%) and non-farm payrolls by 168,000 (0.1%). Source: The Economist Immigration and thermostatic politics (Sarah O’Connor in the FT) A strange thing happened a year and a half ago. No sooner had Americans elected Donald Trump as president on an explicitly anti-immigration platform than US public opinion began to swing much more favourably towards immigration. … to political scientists who study “thermostatic” politics, this development is no surprise at all. Public opinion often moves against the prevailing party, especially if they are perceived to have gone “too far” in one direction. The phenomenon was first explored in the 1990s with reference to fiscal policy, but in recent years it has been particularly evident in the realm of immigration policy. While these swings in opinion polls can make it seem as if people don’t know their own minds, they can be a useful democratic check on governments by sending bright flashing warning lights when policies stray too far from the public’s comfort zone. The problem comes when politicians misinterpret those signals. When people tell pollsters they want less immigration, or think it is bad for the country overall (or the converse), they are often expressing an opinion about how things appear to be going in that moment relative to their preferences, rather than a deep shift in their underlying views. According to Alexander Kustov, a political scientist, most Americans’ views are quite stable and moderate: they support immigration that is controlled and in the national interest, and oppose flows that are disorderly or under-enforced. In the US, he argues the Trump administration over-interpreted dissatisfaction with high immigration under Joe Biden, and implemented policies that went too far for many voters. “People don’t necessarily change their idea about their ideal immigration policy, but they can react to what the government is currently doing,” he told me. “A lot of people are not happy with what the Trump administration are doing — right now we’re not talking about border enforcement, we’re talking about people not just getting harassed, but killed.” But similarly, he added, pro-immigration advocates would be making a mistake to interpret the recent, more favourable swing towards immigration as a deep-seated ideological shift in attitudes. The recent history of UK immigration policy offers another cautionary tale. After the 2016 Brexit referendum, public concern about immigration fell. This was partly because net migration statistics declined, but also because people felt a sense of catharsis and control, says Sunder Katwala, director of British Future, a think-tank. By 2019, the public ranked immigration as only the ninth biggest issue of concern, according to Ipsos polling. But when the Conservative government liberalised visa routes for students and care workers between 2019 and 2022, that helped net migration to surge. And so, too, did public concern. Today’s Labour government has implemented another sharply restrictive turn in immigration policy. As Kustov and researcher Caitlyn Yates argue, thermostatic public opinion should be a useful check on politicians. Instead it seems to have helped to magnify the pendulum swing in the UK. The government over-interprets and overreacts to a change in public opinion, which reacts in turn, prompting a sudden swing the other way. Source: Financial Times HEY READERS, THANK YOU for opening the Chartbook email. I hope it brightens your day. I enjoy putting out the newsletter, but tbh, what keeps this flow going is the generosity of those readers who clicked the subscription button. If you are persuaded to click, please consider the annual subscription of $50. It is both better value for you and a much better deal for me, as it involves only one credit card charge. Why feed the payments companies if we don’t have to. Subscribe Anna Airy, Shop for Machining 15-Inch Shells: Singer Manufacturing Company, Clydebank, Glasgow, 1918 Racing for a vaccine … we have been here before! The deadly Ebola outbreak in two African countries driven by a virus species with no vaccine has triggered an urgent search for a potential jab, in a test of troubled global efforts to avert threats posed by emerging diseases. A World Health Organization advisory group is due to would meet on Tuesday to recommend candidate jabs to prioritise for clinical trials, the global health body said. It will assess data including an analysis by the Coalition for Epidemic Preparedness Innovations (Cepi), which was set up after failures in the international response to a previous Ebola crisis. The latest Ebola outbreak in Democratic Republic of Congo and Uganda has infected hundreds of people and killed more than 80, health authorities say. Cepi’s reaction will be a crucial indicator of its progress towards its wider goal of producing vaccines for pandemic threats in just 100 days, despite steep cuts to international health funding. “If there was ever a time that we could show the world why Cepi is needed and show the world why the 100-day mission is needed, it’s now,” Nicole Lurie, the organisation’s executive director for preparedness and response, told the FT. “We’re happy to accept that responsibility, but obviously we need help from partners — particularly financial help in the long run.” DR Congo and Uganda would make the final decision on whether to press ahead with any vaccine candidates endorsed for clinical trials by the WHO experts, the global health body said. “Other ethical and community acceptability issues will be considered,” said the WHO, which declared the latest outbreak a public health emergency of international concern on Sunday. “This will be important to make sure that the trial, if it happens, will be adequately communicated to the population.” Lurie said Cepi had provided information from a survey of research teams and companies working on drugs that might be effective against the Bundibugyo virus behind the outbreak. The organisation hoped soon to announce partners in the quest for a jab, she added, although she declined to give a timescale for when one might be developed. Cepi’s Nicole Laurie said global health bodies were ‘getting some live-fire drills’ with hantavirus and the latest Ebola outbreak. The hunt for a vaccine should be helped by scientific advances including the use of artificial intelligence to find drugs active against viruses, Lurie said. Existing jabs against the Zaire Ebola virus responsible for many previous outbreaks might provide a basis for tackling the Bundibugyo species, she added. “We’ll see how far and how fast we can get,” Lurie said, adding that Cepi had done preliminary work recently on a possible jab for the rat-borne hantavirus responsible for a recent fatal outbreak on a cruise ship. “Both with hantavirus and now with Ebola, [we] are getting some live-fire drills.” Source: Michael Peel in the Financial Times Dad-chat is coming for dad-books. (By Pamela Paul and Jeffrey A. Trachtenberg in the WSJ) They were the go-to gifts for Father’s Day: a book about some little-known chapter of World War II, the sweeping narrative of a shipwreck, perhaps the latest presidential biography. These days, dad books are a dying breed. Nonfiction book sales have been in decline for the past four years, and are now the most challenged segment of the print book market. Publishers say certain types of books still fare well—including celebrity memoirs and religious titles. But in recent years, print sales in such categories as biography, current affairs and business and economics—what publishers refer to as “serious nonfiction” and which tend to resonate especially with men—have fallen considerably. Sales of nonfiction print titles were down nearly 8% through May 9 this year, and sales of books about politics and current affairs were down 19%, according to book tracker Circana BookScan. Publishing has long been subject to cyclical changes, with trends in format and genre taking over bookshelves in grand sweeps. (Remember the adult coloring-book craze? Or the stratospheric rise of romantasy?) But many in publishing believe the decline in serious nonfiction is more existential. “The trend couldn’t be clearer,” said Jonathan Karp, the former chief executive of Simon & Schuster and publisher of the new Simon Six imprint. “This is a sea change and people should wake up and realize we’re living in a new world.” One culprit for the shift: a new media diet for fans of more serious nonfiction. … Sixty-two percent of men and 54% of women consumed a podcast in the prior month, according to a recent survey by Edison Research at SSRS, up from 46% and 39%, respectively, in 2023. “When we have internal meetings to talk about this problem, it always comes around to podcasts,” said Jonathan Burnham, president and publisher of the Harper Group at HarperCollins Publishers. “The man who wants to read American history is now tuning into one of the many good podcasts about history that lends the quiet attention to a serious subject he’s looking for. It makes the idea of sitting down with a 700-page Ron Chernow book less appealing. You’ve scratched that itch.” Source: Wall Street Journal Remarkable report by Novara from the nationalist rally in London in mid May. Anna Airy, Leopard Moth and Plums, 1915 If you’ve scrolled this far, you know you want to click: Subscribe
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AI & Science: What Is the Future of Discovery?
Continued progress in artificial intelligence, its expanding usefulness in science, and its contributions to landmark advances suggest that we may have entered a new era of AI for science.The breakthroughs so far—such as predicting the structure of practically every known protein, with profound implications for our understanding of biology, health, and the treatment of disease—are notable not only for what was achieved but also how it was achieved and what that suggests for scientific progress. This special double issue of Dædalus poses the question: What is the future of scientific discovery in this new age of AI? Thirty-three scientists responded. Bringing perspectives from life sciences and medicine, cognitive science and neuroscience, the physical and earth sciences, chemistry and materials science, computer science, mathematics and the social sciences—they draw on their work at the frontier of AI and science. The authors write with an eye to the future, not just the present. They explore what is being achieved and what possibilities lie ahead; examine AI’s limitations and efforts to move forward; and investigate the larger implications of AI-assisted science—on how science is done, the role of the scientist, and the scientific method, as well as the challenges and complexities involved.The authors together exemplify a long-standing bidirectional relationship: AI advancing science, while science advances AI. Where that relationship will take us—a golden age of discovery? New scientist-machine collaborations? Autonomous labs? Discoveries without human understanding?—is a future we are only beginning to imagine, and one we must also shape if the beneficial possibilities are to be realized.Image: UMAP sculptures visualizing three Dædalus volumes on artificial intelligence. © 2026 by Refik Anadol.
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