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Legal AI startups face bubble fears as EvenUp doubles down
Legal AI startups like EvenUp and Harvey face bubble risks as law firms, Stanford and investors test new tools at LegalTech Fund Summit.
OpenAI Gives Businesses New Tools to Reach ChatGPT Users
OpenAI is launching a new suite of tools that lets companies manage their presence on the platform, track customer engagement and deploy artificial
12 New Klein Tools To Add To Your Wishlist In 2026
Klein Tools continues to expand its catalog with new tools for professionals and DIYers alike, including screwdrivers, ratchet sets, stud finders, and more.
Dropbox’s New Tools Will Organize Your Messy Files. Business Owners Could Avoid Hours of Busy Work
Agentic capabilities are coming to Dropbox, the cloud storage platform with more than 700 million registered users worldwide.
DoorDash sees limited AI orders, but explores new tools
DoorDash CEO Tony Xu discusses AI agents like Meta's Muse, revealing low order numbers but plans for enhancing DoorDash's AI tools.
Apple Updates Creator Studio With New Tools and AI Features
Apple today announced a new update to its Creator Studio suite of apps, adding a number of additional features and tools across Mac, iPad, and iPhone. Amongst the new features, Final Cut Pro for Mac now includes built-in MotionVFX, which was previously a third-party content maker. The integration brings over thousands of effects, plug-ins, transitions, templates, titles and motion graphics tools, including rotoscoping, tracking, and color grading.
New Tools and Fresh Thinking Are Reshaping the Science of Addiction
A new Frontiers Research Topic argues that biosensors, longitudinal phenotyping, and transdiagnostic biomarkers are transforming addiction from a static label into a dynamic, mechanism-based science.
New Tools Let Users Edit and Load Modified VBIOS on GeForce RTX GPUs Without Flashing
A developer who goes by Panchovix has released three tools that let NVIDIA GeForce RTX 50, RTX 40, and RTX 30-series owners run a modified VBIOS without writing anything to the card's flash chip. The first is a VBIOS editor for Windows and Linux that can change power limits, voltage ceilings,...
This new theory on how AI 'thinks' could impact whether it kills us
We may be closer to understanding how AI models think, giving researchers new tools to ensure they don't go rogue.
Science can't conquer HIV without dismantling barriers
OPINION: New tools can transform HIV prevention and treatment. Their reach depends on confronting the barriers that keep people from care.
Teladoc Health unveils new AI capabilities within Solo platform for hospitals
Teladoc Health announced Wednesday the launch of two new artificial intelligence capabilities within its enterprise smart care platform Solo. | The two new tools aim to help health systems surface timely patient insights into their care environments while reducing technology fragmentation, executives say.
Should Aging Be Called a Disease? Scientists Are Rethinking What It Means to Grow Older
What if the next big target in medicine is getting older itself? Researchers are taking that possibility seriously, with new tools, new clinics, and growing FDA attention. Instead of waiting for diabe...
Amazon Accelerate 2026: New Tools Give Small Sellers More Capacity, Simplicity, and Global Reach - Small Business & Entrepreneurship Council
By Karen Kerrigan – Each year, the Amazon Accelerate event provides a window into where e-commerce is headed and announcements are made about new tools and capabilities that are being developed for small sellers. This year’s event was held in Seattle from September 22-24, and several significant innovations were announced about AI agents, multichannel-commerce […]
Why dementia is preventable – and the new tools that can reduce your risk
On World Alzheimer’s Day, a look at advances in dementia diagnosis and treatment, and why much of the risk may be within our own control.
That security patch date on your Android phone is no longer the full story
Google has released new tools allowing Android apps to get a much more accurate picture of how secure your phone really is.
Science council plots diplomacy push for fractured world
Peter Gluckman says the multilateral system needs new tools to survive an age of rivalry
Business Tech Roundup: Will AI Kill Us In The Next Few Years?
An Anthropic researcher has a warning, ChatGPT helps people draw better and Pinterest rolls out new tools. Meta launches Muse.
American Board of Radiology taking cautious approach to AI
Rather than moving quickly to adopt new tools, the Tucson, Arizona-based doc-certification organization is studying developments, engaging experts and establishing guardrails before introducing any change.
IRS expands Business Tax Account with new online features for eligible businesses
New tools allow businesses to view digital notices, download EIN verification and manage payment plans online
Can the pioneer of fake image detection keep up with AI?
The godfather of digital forensics, Hany Farid, is developing new tools to detect AI-generated imagery
Understanding the exposome
The world around us influences our health in countless ways. New tools and approaches are helping scientists measure our environmental exposures—both good and bad—on a large scale in the hopes of improving prevention and treatment strategies.
Why AI Is Creating New Cybersecurity Risks For Healthcare
AI is helping hospitals improve diagnostics and patient care, but it's also giving cybercriminals new tools to target healthcare systems.
Chase Offers Small Businesses More Credit Insights
Chase has introduced new tools for small business in its Chase for Business mobile and online hub. The updates, announced Tuesday (June 9), include the
Tim Cook Delivers Farewell Remarks at His Last Apple Keynote as CEO
Tim Cook closed out what is expected to be his last keynote as Apple's chief executive officer today with some emotive final remarks. Wrapping up a pre-recorded video message, Cook reflected on his tenure at the company. "Some of the highlights of my time as CEO have been events like this, sharing powerful new tools with all of you," he said, adding that what developers create with Apple's platforms has been "a constant reminder that imagination has no limits".
Microsoft drives developers toward native Windows apps at Build 2026
Microsoft wants more WinUI 3 apps across Windows 11, and Build 2026 shows how developers can get there with new tools, agents, and hardware.
AI Training For Small Businesses Goes Nationwide
Free AI training from the U.S. Chamber and new tools from Anthropic are arriving just as small business formation surges and the AI adoption gap begins to close.
Google Advances AI for Science with New Tools and Tech
Google is launching a series of new tools to help scientists leverage AI technology as a force multiplier to accelerate the pursuit of scientific knowledge and discovery. In addition to the collection of tools under the Gemini for Science banner, it is also launching Science Skills, which centralizes data from more than 30 life science […]
Anthropic wants small businesses to use Claude
The company launched new tools designed for lean teams.
Little Rock Regional Chamber to host Small Business Summit, Impact Awards on May 6
Small business owners across Arkansas will have a chance to swap ideas, pick up new tools and maybe even snag an award when the Little Rock Regional Chamber hos
How to get clinical and ops staff to adopt new tech – a major health IT challenge
"It's coming at them at a very fast pace," says Broward Health CIO Steven Travers, who advises healthcare organizations to ensure new tools fit both what an organization is is trying to accomplish, and the existing processes of frontline staff.
Google Photos adds new touch-up tools for 'quick' fixes
You can use the new tools to remove blemishes, refine skin texture, brighten eyes, or whiten teeth in photos.
New tools drive scientific discovery: evidence from all nobel-prize and major non-nobel breakthroughs
Humanities and Social Sciences Communications - New tools drive scientific discovery: evidence from all nobel-prize and major non-nobel breakthroughs
“AI polls” are fake polls
A few weeks after Donald Trump’s second presidential win, I took the train up from London (where I was living at the time) to Oxford to attend a conference on polls and forecasts of the 2024 election. Most of the attendees were pollsters or academics, but I also watched presentations from Aaru and Electric Twin, two companies that do what is interchangeably called synthetic sampling, silicon sampling, or synthetic audiences. Stripped of startup jargon, that means they use large language models (LLMs) to simulate responses to public opinion polls by having AI agents take on the role of survey respondents. I had already heard of Aaru thanks to some articles with eye-catching headlines like “No people, no problem: AI chatbots predict elections better than humans” in the months leading up to Election Day. The founders were making some big, some might even say far-fetched claims, such as: “within two years, we will simulate the entire globe — from the way crops are grown in Ukraine to how that impacts production of oil in Iraq, trade through the strait of Malacca, and elections for the mayor of Baltimore.” When Semafor asked Aaru’s cofounders — Cameron Fink and Ned Koh — about my boss, they said “we respect all those who came before us.” Nate (as he so often does) shared his thoughts on Twitter: Fink and Koh were relatively good-natured about this back-and-forth when we spoke at Oxford. They even offered to mail me one of the t-shirts featuring Nate’s quote they apparently had made. I never took them up on the offer, which I now somewhat regret. These synthetic sampling companies fell off my radar for a while, but they do still exist. In fact, Aaru recently received a $1 billion valuation. Is what they’re doing anywhere close to the most important frontier in AI development? Not by a longshot, especially when Anthropic just developed a model so adept at exploiting software vulnerabilities that it’s only being released to 40 companies. Still, silicon sampling is increasingly finding its way into public polling. Axios reported in March that “a majority of people trust their own doctors and nurses” based on findings from Aaru — without mentioning that the “people” in that sentence were actually LLMs. Around the same time, the Public Sentiment Institute “boosted” their online sample of 373 real survey respondents with 114 AI agents.1 (Spoiler alert: even the co-founder of Electric Twin doesn’t think that’s a particularly defensible approach.) Polling companies like Qualtrics and Ipsos are also developing synthetic data panels. So, what should we make of these … “polls”? Let’s get one thing out of the way: whatever they are, they’re not polls in the way that term is usually defined. Subscribe You can’t replace polls with AI On one hand, using LLMs to essentially make up fake survey respondents sort of sounds like the dumbest idea ever, one that will at best imperfectly replicate real polls while introducing all sorts of biases. On the other hand, with LLMs improving at a remarkable, perhaps even alarming rate, maybe that means I’m a dinosaur at the ripe old age of 24 because I still want to rely on polls that talk to actual people. I’m not going to argue that synthetic samples are completely useless. In fact, as I’ll return to later, there is evidence that some techniques can replicate topline survey results quickly and cheaply. But the marketing from certain companies can be slightly optimistic. “No traditional poll will exist by the time the next general election occurs,” said Fink in 2024. We’re just 206 days away from the midterms, and based on the fact that I still have to collect a bunch of polls every day, I’d say he should have run that prediction by a sample of AI agents before the interview.2 To see why synthetic samples can’t replace polls, here’s a quick primer on how they work. The simplest version of these models involves taking a LLM (like ChatGPT or Claude), giving it a demographic profile (e.g., a white, college-educated woman who lives in Utah and makes $70k a year), and then asking it to respond to a survey question. You repeat that process a few thousand times using different demographic profiles and end up with a sample of synthetic survey responses. The actual models used by private companies are more sophisticated than this, usually because they incorporate more hypothesized demographic characteristics for each agent and provide them with extra information. Aaru, for example, feeds agents a diet of news and information they’d be likely to consume, while Electric Twin incorporates their customers’ proprietary data about the audience they’re trying to replicate. The way Ben Warner, the co-founder of Electric Twin, explained it to me was “we have a large amount of data on […] for instance, 5,000 people. Can we make an accurate prediction of how they would respond to another question?” Still, it should be obvious why synthetic samples can’t replace polls. Polling is fundamentally a data collection process. We might use surveys to make predictions by feeding them into election forecasts, but the main purpose of a poll isn’t prediction, it’s gathering new data about what people think and how they feel. Silicon sampling, on the other hand, produces no new data. It’s simply a model: you input LLM training data, demographic prompts, and a bunch of other information, and it spits out a prediction for what a poll would say. We love models here, but models aren’t polls. That difference is an important philosophical sticking point for most pollsters I talk to. “I think politics should stay away from [synthetic sampling], because we’re trying to […] represent the voice of the people,” said Natalie Jackson, a vice president at GQR Insights. Democratic pollster John Hagner told me: “I think I’m just incredibly skeptical of this idea. I don’t think it’s research. At that point, you’re asking the machine to tell you what you already believe.” Hagner has seen some presentations of early synthetic sampling experiments, but so far, “if it’s being used in a campaign, people are keeping it incredibly quiet.”3 But Eli, I hear you saying, aren’t polls themselves increasingly governed by modeling decisions? Indeed they are: pollsters’ choices on which sampling method to use, how to define their likely voter models, and how to weight their samples can and do lead to dramatic differences in the results they publish. Aaru even referenced these limitations in the methodology statement included with that maternal mortality “poll” — although I’m using the term “methodology statement” loosely here, because it doesn’t really explain how the model works at all. We can ignore the (frankly preposterous) implication that synthetic sampling isn’t subject to a separate set of biases. The important point is that there’s still a meaningful difference between using weighting and other statistical techniques on actual polling data and using a model to predict what a poll would say. The latter is far closer to election forecasts or techniques like MRP — potentially useful models, but not a replacement for polls.4 To be fair, other synthetic sampling companies are perfectly happy with the distinction between polls and models. Warner compared polling and synthetic sampling to different tools in a toolbox. “The mistake I think we make is we think that these new tools should either work in exactly the same way or somehow replace these old tools,” he said. “Rather than thinking of it as, okay, so we’ve always had the hammer, we’ve always had the screwdriver, now we’ve got a saw. But don’t use a saw to try [to] do the job of a hammer.” A quick comment from Nate Eli didn’t ask me for a comment — rather rude of him, don’t you think? But since I’m editing this story, I figured I’d add a few quick thoughts rather than putting words in his mouth. Beyond the frequently misleading marketing, what bothers me about the AI “poll” hype is that as AI tools make statistical inference cheaper and/or better (note that these are not synonyms) that actually increases the comparative value of collecting original data. You might be able to train a model to make a reasonable estimate of what some hard-to-reach poll respondent would say — say, a young Black man who voted for Trump. (Such a person checks a number of boxes for a voter who is usually hard to reach in surveys.) Indeed, this is closely related to what models like the Silver Bulletin forecast already do. They essentially smooth out the kinks in noisy survey data by making inferences based on past voting patterns or national polls or surveys of other states. But you don’t actually know what these voters think unless you’re reaching them directly. If there’s a shift in opinion among this subgroup, you’re not going to detect it. So if I were running a campaign, I’d invest more in going the extra mile to find a representative sample of those voters. And then I’d hire some smart quants — or Claude? — to figure out the implications for campaign strategy based on proprietary data that my competitors didn’t have access to. -Nate Silver Are these models any good? If synthetic surveys are just a new type of model, the next obvious question is whether the models are at least accurate. The answer very much depends on who you ask. On one end of the spectrum, you have the maximalist argument that synthetic sampling is more accurate than actual polls. “It’s an incredibly challenging problem to go to someone and say ‘hey, we’re going to be more accurate at predicting human behavior than you, even when you talk to your customers directly’,” Koh recently told CNBC. In his view, synthetic sampling isn’t a saw to polling’s hammer, it’s “magic.” There’s certainly evidence that synthetic samples can replicate certain survey toplines. But if Aaru does have any examples of their approach outperforming the polls, they’re keeping those to themselves.5 Aaru’s 2024 election model, for example, had Kamala Harris leading in Michigan, Nevada, Pennsylvania, and Wisconsin on November 4th. And although they’ve since taken down their forecast page, they gave Harris a 50.5 percent chance of winning the race on November 2nd.6 After the election, Fink told Semafor he was happy enough with those results because they were “within margin of error,” a term that is completely meaningless when applied to a “sample” of AI agents. And of course, Aaru says their models have improved since 2024, so supposedly now they’d be more accurate than the polls? Still, their stronger argument is on cost: “We are significantly faster and cheaper than traditional polling, and still more accurate,” said Fink. The first two claims are undeniably true, but the third brings us to the opposite end of the spectrum. Both Jackson and Hagner are skeptical that these models are reliable for anything beyond replicating common survey toplines. “I just […] don’t think the machines are what we want when we’re looking for nuanced views. My example on this is people in Arizona and Nevada in 2024 who voted for Trump and voted for expanding abortion in their states on ballot initiatives,” said Jackson. Hagner identified another issue. Maybe the synthetic respondents, like sycophantic LLMs, are inhuman in one important way: they’re too nice. “The reports that have come through at the meetings that I’ve been at are that the early experiments on this, they cannot get respondents to be as racist or sexist or, frankly, as negative as human respondents,” he said. Academic research mostly agrees on this point. While there are some papers that show promising results when using LLMs to replicate polling data, most show that LLMs suffer from various quirks like producing too few “don’t know” responses and can seriously overpredict the favorability of politicians like Donald Trump and Kamala Harris. They also seem to struggle with too little variation between demographic subgroups, so the difference in predicted opinion between Democrats and Republicans, for example, is too small. When I asked Warner about these studies, his response to these papers was that just because academics can’t get synthetic sampling to work doesn’t mean that the technique doesn’t work in general. “Actually, the argument is, okay, yours does not [work]. That does not mean […] for this complex set of machinery, which uses a lot of investment, a lot of time, a lot of money, you can’t get it to work.” Cards on the table, I’m somewhat sympathetic to this argument because academics aren’t exactly great at making election forecasts. Usually, the people with skin in the game are the most accurate. Warner’s argument is that the approach Electric Twin takes — which includes, for example, making multiple predictions for each synthetic respondent using different models and prompts and subsequently averaging those to get a final prediction in a sort of ensemble forecast — produces better results than the simpler academic models. Warner shared a comparison between his method and the method from a recent academic paper with me, and Electric Twin was indeed able to get more accurate replication. But even still, he acknowledged that synthetic sampling “is not a crystal ball.” “If you asked me, do I think using other data sources will be more accurate than asking somebody who they will vote for, I would probably say no. But if you asked me ‘would your system be useful for our turnout modeling today?’ I would say yes.” For better or worse, it looks like the method is already getting more popular in the market research world. Most of the clients Aaru touts these days are businesses like EY and McDonald’s. And AI will probably begin to pop up in other parts of the political polling process. Pollsters are already using it to code open-ended survey responses, and some firms, like YouGov, are testing using LLMs to ask survey respondents questions. More worryingly, one danger to actual polls is that AI agents can be used to infiltrate online surveys. Most online polls use various checks to prevent that from happening, but there’s conflicting evidence on how effective those filters are and how prevalent AI agents currently are in online panels. If those agents ever become impossible to detect, it might spell the end of online polling, but the solution isn’t to replace all of your respondents with ChatGPT. Silver Bulletin is a reader-supported publication. To receive new posts and support our work, consider becoming a subscriber. Subscribe 1 That particular poll obviously doesn’t meet Silver Bulletin standards for aggregation. But we exclude all Public Sentiment Institute polls from our averages because we classify them as an amateur polling firm. 2 You could argue that Fink meant the next presidential election, but (a) I’m also confident we’ll still have real polls in 2028 and (b) in that case he should have asked an LLM to define “general election.” 3 Quick caveat: that’s reporting from a Democratic pollster. It’s possible that Republicans are more willing to use AI in political campaigns. 4 Indeed, Silver Bulletin does not include “polls” produced by MRP in our forecasts or averages, and we think it’s extremely misleading when their practitioners describe them in a way that suggests original data had been collected among a large number of states or Congressional districts. 5 A recent report from Aaru and EY did show two examples of a synthetic estimate being closer than a survey to a real-world benchmark — but I’d take those findings with a grain of salt because the report reads more like an ad and didn’t involve any sort of prediction being made ahead of time. 6 For comparison, our odds for Harris on the same day were 48.2 percent.
Saving biodiversity: Can innovation stop extinction?
Nearly a third of all species are at risk. New tools—from biodiversity credits to AI like BirdNET and measures against the Asian tiger mosquito—aim to protect ecosystems and human health.
Science in the age of AI
The transformative potential of new tools was the emphasis of Virginia Tech's Leaders+ discussion in Alexandria with OpenAI Vice President for Science Kevin Weil. The event was attended by more than 150 researchers, graduate students, and other members of the scientific and industry communities.
Google Gemini Adds Tool to Make It Easier to Switch from ChatGPT
Google released new tools for its Gemini artificial intelligence assistant that will let users upload chat history and context from other AI apps, a move to lure users from rivals like OpenAI’s ChatGPT and Anthropic PBC’s Claude.
Kali Linux 2026.1 released with 8 new tools, new BackTrack mode
Kali Linux 2026.1, the first release of the year, is now available for download, featuring 8 new tools, a theme refresh, and a new BackTrack mode for Kali-Undercover.
German Health Minister Nina Warken and WHO Hub in Berlin highlight 2025 achievements
Germany’s Federal Minister of Health, Nina Warken, visited the WHO Hub for Pandemic and Epidemic Intelligence in Berlin today to review progress and launch its 2025 Annual Report. The report highlights advances in using artificial intelligence, data science and pathogen genomics to strengthen global preparedness for future pandemics.In 2025, the WHO Hub in Berlin worked with more than 160 Member States and over 190 partners to help countries and organizations develop new systems and tools to detect and understand new public health threats as quickly as possible, whenever and wherever they occur.BMG to confirm whether they wish to contribute a quote. “Detecting outbreaks early is one of the most effective ways to save lives and prevent epidemics from becoming global crises,” said Federal Minister of Health Nina Warken. “Germany is proud to host and support the WHO Hub for Pandemic and Epidemic Intelligence. Its work strengthens our safety at home and helps protect people worldwide.”Artificial intelligence is increasingly transforming the detection of outbreaks. In 2025, the Hub launched an upgraded version of the Epidemic Intelligence from Open Sources (EIOS) system, which uses enhanced AI functions to scan global online information in real time and help experts quickly identify unusual health events. The system is now used by 120 countries.To better anticipate health threats, countries need information beyond traditional health data. The Hub supports countries in implementing Collaborative Surveillance, which integrates data on climate, animals, travel, and population movement to provide a more comprehensive and real-time understanding of health threats.The Hub also expanded global access to pathogen genomics, which helps scientists detect new pathogens, such as viruses and bacteria, understand how they spread and how dangerous they may become. Through the International Pathogen Surveillance Network (IPSN), the WHO Hub in Berlin worked with 309 partners in 101 countries to expand access to these technologies.“We are in a new era of global health threats, and we need new tools to face tomorrow’s challenges,” said Dr Chikwe Ihekweazu, Executive Director of the WHO Health Emergencies Programme. “The WHO Hub in Berlin helps countries use data and technology more effectively so they can identify risks earlier and respond faster. No country can address these threats alone. Strong cooperation remains our best defence.”“Berlin offers an ideal environment for our work. We collaborate closely with world-leading institutions such as the Robert Koch Institute and the Charité Center for Global Health,” said Dr Oliver Morgan, Head of the WHO Hub for Pandemic and Epidemic Intelligence. “Germany has supported the WHO Hub since its establishment, and we are pleased to welcome Federal Minister Nina Warken to the Hub today. This strong partnership helps us advance innovation in pandemic and epidemic intelligence and better support countries to prepare for future health threats.”The Hub is expanding the use of advanced analytics and mathematical modelling to forecast how outbreaks may develop and to assess which response measures are most effective. Through its Collaboratory, the Hub connects modelers and analysts with governments to ensure their work addresses real public health needs. In 2025, the community grew to 1300 members from 50 countries and 200 institutions. An AI-powered pandemic simulator, currently in the prototyping phase, will help decision-makers compare outbreak scenarios and help identify effective disease control measures.
IRS updates Tax Pro Account with new digital tools for business tax practices
The new tools create a digital foundation for future enhancements aimed at tax professionals.
CalMatters’ “visionary” co-founder, Dave Lesher, retires
Co-founder Dave Lesher turned CalMatters into one of California’s most influential newsrooms — and launched new tools to make your government transparent
Windows 11 gets a December Insider update packed with new features and AI upgrades — reveals Microsoft’s next big push. Here's everything that is new.
The latest Windows 11 Insider build quietly adds new tools, UI tweaks, and deeper AI integration. Some of these changes are big.
"MicroProse and Geoff Crammond Reunite to Revive a Racing Legend"
MicroProse is excited to announce its renewed partnership with legendary game developer Geoff Crammond, creator of some of the most influential racing simulation games of the 1990s and early 2000s. Together, we are bringing back his groundbreaking racing game engine in a re-release of the original game technology, enhanced with updates, new tools, and Steam Workshop support, through the upcoming Geoff Crammond Racing series: GCR1, GCR2, GCR3, and GCR4, scheduled to release in 2026. These titles are being reintroduced under new names to reflect our independent direction and to ensure full separation from any official motorsport licensing. While the names are new, the core simulation engine, physics systems, and pioneering gameplay features developed by Geoff Crammond remain at the heart of each release. Geoff Crammond’s original work helped define the foundations of modern racing games, introducing innovations such as advanced real-time physics, highly configurable driving assists (including the ideal racing line, steering help and auto braking), realistic AI driver behaviour, deep telemetry analysis, comprehensive car setup systems, extensive wet weather system, and the list goes on. The GCR series proudly carries this legacy forward. Steam Workshop support will enable the community to create and share custom tracks, cars, liveries, teams, drivers and more. This reunion marks the beginning of a long-term partnership between MicroProse and Geoff Crammond, with further announcements in the series to come. MicroProse is officially back on the track at full speed. GCR1 Steam Page GCR2 Steam Page GCR3 Steam Page GCR4 Steam Page -- MicroProse, founded in 1982, is a world-famous simulation software company known for developing groundbreaking classics and new blockbuster titles such as Falcon, HighFleet, B-17 The Mighty Eighth, Ground Branch, Gunship and many more! Today, MicroProse is not only remaking select classics from its past but also paving the road to next-generation, state of the art games that will create the memories and experiences of new generations of gamers.
Space is filling with junk and scientists have a fix
Earth’s orbit is getting crowded with broken satellites and leftover rocket parts. Researchers say the solution is to build spacecraft that can be repaired, reused, or recycled instead of abandoned. They also want new tools to collect old debris and new data systems that help prevent collisions. The goal is to make space exploration cleaner and more sustainable.