Americans' confidence in the mass media has edged down to a new low, with just 28% expressing a "great deal" or "fair amount" of trust in newspapers, television and radio to report the news fully, accurately and fairly, according to Gallup. From the report: This is down from 31% last year and 40% five years ago. Meanwhile, seven in 10 U.S. adults now say they have "not very much" confidence (36%) or "none at all" (34%). When Gallup began measuring trust in the news media in the 1970s, between 68% and 72% of Americans expressed confidence in reporting. However, by the next reading in 1997, public confidence had fallen to 53%. Media trust remained just above 50% until it dropped to 44% in 2004, and it has not risen to the majority level since. The highest reading in the past decade was 45% in 2018, which came just two years after confidence had collapsed amid the divisive 2016 presidential campaign.

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A hacking group claims to have pulled data from a GitLab instance connected to Red Hat's consulting business, scooping up 570 GB of compressed data from 28,000 customers. From a report: The hack was first reported by BleepingComputer and has been confirmed by Red Hat itself. "Red Hat is aware of reports regarding a security incident related to our consulting business and we have initiated necessary remediation steps," Stephanie Wonderlick, Red Hat's VP of communications told 404 Media. A file released by the hackers and viewed by 404 Media suggested that the hacking group may have acquired some data related to about 800 clients, including Vodafone, T-Mobile, the US Navy's Naval Surface Warfare Center, the Federal Aviation Administration, Bank of America, AT&T, the U.S. House of Representatives, and Walmart.

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Tech companies are struggling to fill AI-specialized roles despite a surplus of available tech talent. U.S. colleges more than doubled the number of computer science degrees awarded between 2013 and 2022. Major layoffs at Google, Meta, and Amazon flooded the job market. The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than last year. The disconnect stems from companies seeking workers with specific AI expertise. Runway CEO Cristobal Valenzuela estimates only hundreds of people worldwide possess the skills to train complex AI models. His company advertises base salaries up to $490,000 for a director of machine learning. Daniel Park's startup Pickle offers up to $500,000 base salary and expects candidates willing to work seven days a week. The WSJ story includes the example of one James Strawn, who was laid off from Adobe over the summer after 25 years as a senior software quality-assurance engineer. The 55-year-old has had one interview since his layoff. Matt Massucci, CEO of recruiting firm Hirewell, told the publication companies can automate some low-level engineering tasks and redirect that money to high-end talent.

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More than 100,000 people were sent to hospitals due to heatstroke in Japan between May 1 and Sunday, according to preliminary data from the Fire and Disaster Management Agency. Bloomberg, via Japan Times: The number is the most on record, according to NHK. Transport to hospitals of patients linked to heatstroke over the period rose almost 3% to 100,143 from a year earlier as Japan saw its national temperature record broken twice in a matter of days. The country's average temperature during this summer was the highest since the statistic began being compiled in 1898, the nation's weather agency said last month. Heat waves around the world are being made stronger and more deadly due to human-caused climate change. Government officials in August pledged to boost public health protections and encouraged the installation of more air conditioners in school gymnasiums and the use of cooling centers in communal spaces like libraries. New rules came into effect this summer that require employers to take adequate measures to protect workers from extreme temperatures.

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Major health insurers are threatening to drop renowned cancer centers from their networks during contract negotiations, Memorial Sloan Kettering Cancer Center's president and CEO Selwyn M. Vickers and chairman Scott M. Stuart wrote in a story published by WSJ. Memorial Sloan Kettering Cancer Center reported that both Anthem Blue Cross Blue Shield and UnitedHealthcare prepared to terminate network agreements while patients underwent active cancer treatment. FTI Consulting found that 45% of 133 provider-payer disputes in 2024 failed to reach timely agreements. The disruptions have affected tens of thousands of patients. Research published in the Journal of the National Cancer Institute found that care disruptions lead to more advanced-stage diagnoses and worse outcomes. Similar contract disputes involved Mayo Clinic, Johns Hopkins University and University of North Carolina Health. New York lawmakers introduced legislation this year requiring insurers to maintain coverage for cancer patients during negotiations and until treatment concludes. Memorial Sloan Kettering's leadership described the practice as using patients as bargaining chips despite record insurer profits.

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Google has laid off over 100 employees in design-related roles, including user experience research and cloud design teams, as part of broader cost-cutting measures to prioritize AI infrastructure. CNBC reports: Earlier this week, the company laid off employees within the cloud unit's "quantitative user experience research" teams and "platform and service experience" teams, as well as some adjacent teams, according to internal documents viewed by CNBC. The roles often focus on using data, surveys and other tools to understand and implement user behaviors that inform product development and design. Google has halved some of the cloud unit's design teams, and many of those affected are U.S.-based roles. Some employees have been given until early December to find a new role within the company.

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Scientists have discovered complex organic molecules within the icy plume erupting from Saturn's moon Enceladus, strengthening the case that its hidden saltwater ocean may harbor the conditions for life. The Guardian reports: The sixth largest of Saturn's moons, Enceladus has become one of the leading contenders in the search for bodies that could harbor extraterrestrial life, with the Cassini mission -- which ended in 2017 -- revealing the moon has a plume of water ice grains and vapors erupting from beneath the surface at its south pole. The phenomenon has since been captured by the James Webb space telescope, with the plume reaching nearly 6,000 miles into space. The source of this material is thought to be a saltwater ocean that lies beneath the moon's icy crust. Now researchers studying data from the Cassini mission say they have discovered organic substances within the plume, with some types of molecule detected there for the first time. Dr Nozair Khawaja, a planetary scientist at Freie University Berlin and lead author of the work, said the results increased the known complexity of the chemistry that is happening below the surface of Enceladus. "When there is complexity happening, that means that the habitable potential of Enceladus is increasing right now," he said. Writing in the journal Nature Astronomy, Khawaja and colleagues reported how their previous work had revealed the presence of organic substances and salts within ice grains found in a ring of Saturn, known as the "E-ring," that is composed of material ejected from Enceladus. [...] While the new findings do not show that there is life on Enceladus, Khawaja said they indicate there are complex chemical pathways at play that could lead to the formation of substances that could be biologically relevant. The results, he added, support plans by the European Space Agency (ESA) to investigate the moon for signs of life. "I think all the signals are green here for Enceladus," Khawaja said. The findings add momentum to ESA's proposed mission to directly search for biological signs around 2042. According to the ESA, the mission will consist of an orbiter around Enceladus that will also fly through the plumes, as well as a lander that will touch down in the south pole region of the moon.

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Usually, when we have a "Tales from the Interview" we're focused on bad interviewing practices. Today, we're mixing up a "Tales" with a CodeSOD.

Today's Anonymous submitter does tech screens at their company. Like most companies do, they give the candidate a simple toy problem, and ask them to solve it. The goal here is not to get the greatest code, but as our submitter puts it, "weed out the jokers".

Now our submitter didn't tell us what the problem was, but I don't have to know what the problem was to understand that this is wrong:

int temp1=i, temp2=j; while(temp1<n&&temp2<n&&board[temp1][temp2]==board[i][j]){ if(temp1+1>=n||temp1+2>=n) break; if(board[temp1][temp2]==board[temp1][temp2+1]==board[temp1][temp2+2]) points++; ele break; temp2++; }

As what is, in essence, a whiteboard coding exercise, I'm not going to mark off for the typo on ele (instead of else). But there's still plenty "what were you thinking" here.

From what I can get just from reading the code, I think they're trying to play tic-tac-toe. I'm guessing, but that they check three values in a column makes me think it's tic-tac-toe. Maybe some abstracted version, where the board is larger than 3x3 but you can score based on any run of length 3?

So we start by setting temp1 and temp2 equal to i and j. Then our while loop checks: are temp1 and temp2 still on the board, and does the square pointed at by them equal the square pointed at by i and j.

At the start of our loop, we have a second check, which is testing for a read-ahead; ensuring that our next check doesn't fall off the boundaries of the array. Notably, the temp1 part of the check isn't really used- they never finished handling the diagonals, and instead are only checking the vertical column on the next. Similarly, temp2 is the only thing incremented in the loop, never temp1.

All in all, it's a mess, and no, the candidate did not receive an offer. What we're left with is some perplexing and odd code.

I know this is verging into soapbox territory, but I want to have a talk about how to make tech screens better for everyone. These are things to keep in mind if you are administering one, or suffering through one.

The purpose of a tech screen is to inspire conversation. As a candidate, you need to talk through your thought process. Yes, this is a difficult skill that isn't directly related to your day-to-day work, but it's still a useful skill to have. For the screener, get them talking. Ask questions, pause them, try and take their temperature. You're in this together, talk about it.

The screen should also be an opportunity to make mistakes and go down the wrong path. As the candidate's understanding of the problem develops, they'll likely need to go backwards and retrace some steps. That's good! As a candidate, you want to do that. Be gracious and comfortable with your mistakes, and write code that's easy to fix because you'll need to. As a screener, you should similarly be gracious about their mistakes. This is not a place for gotchas or traps.

Finally, don't treat the screen as an "opportunity to weed out jokers". It's so tempting, and yes, we've all had screens with obviously unqualified candidates. It sucks for everybody. But if you're in the position to do a screen, I want to tell you one mindset hack that will make you a better interviewer: you are not trying to filter out candidates, you are gathering evidence to make the best case for this candidate.

Your goal, in administering a technical screen, is to gather enough evidence that you can advocate for this candidate. Your company clearly needs the staffing, and they've gotten this far in the interview process, so let's assume it's not a waste of everyone's time.

Many candidates will not be able to provide that evidence. I'm not suggesting you override your judgment and try and say "this (obviously terrible) candidate is great, because (reasons I stretch to make up)." But you want to give them every opportunity to convince you they're a good fit for the position, you want to dig for evidence that they'll work out. Target your questions towards that, target your screening exercises towards that.

Try your best to walk out of the screen with the ability to say, "They're a good fit because…" And if you fail to walk out with that, well- it's not really a statement about the candidate. It just doesn't work out. Nothing personal.

But if the code they do write during the screen is uniquely terrible, feel free to send it to us anyway. We love bad code.

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An anonymous reader quotes a report from Wired: Thinking Machines Lab,a heavily funded startup cofounded by prominent researchers fromOpenAI, has revealed its first product -- a tool called Tinker that automates the creation of custom frontier AI models. "We believe [Tinker] will help empower researchers and developers to experiment with models and will make frontier capabilities much more accessible to all people," said Mira Murati, cofounder and CEO of Thinking Machines, in an interview with WIRED ahead of the announcement. Big companies and academic labs already fine-tune open source AI models to create new variants that are optimized for specific tasks, like solving math problems, drafting legal agreements, or answering medical questions. Typically, this work involves acquiring and managing clusters of GPUs and using various software tools to ensure that large-scale training runs are stable and efficient. Tinker promises to allow more businesses, researchers, and even hobbyists to fine-tune their own AI models by automating much of this work. Essentially, the team is betting that helping people fine-tune frontier models will be the next big thing in AI. And there's reason to believe they might be right. Thinking Machines Lab is helmed by researchers who played a core role in the creation of ChatGPT. And, compared to similar tools on the market, Tinker is more powerful and user friendly, according to beta testers I spoke with. Murati says that Thinking Machines Lab hopes to demystify the work involved in tuning the world's most powerful AI models and make it possible for more people to explore the outer limits of AI. "We're making what is otherwise a frontier capability accessible to all, and that is completely game-changing," she says. "There are a ton of smart people out there, and we need as many smart people as possible to do frontier AI research." "There's a bunch of secret magic, but we give people full control over the training loop," OpenAI veteran John Schulman says. "We abstract away the distributed training details, but we still give people full control over the data and the algorithms."

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Renewables generated 54% of the EU's net electricity in Q2 2025, with solar power emerging as the leading source at nearly 20% of the total mix. Electrek reports: According to new data from Eurostat, renewable energy sources generated 54% of the EU's net electricity in Q2 2025, up from 52.7% year-over-year. The growth came mainly from solar, which produced 122,317 gigawatt-hours (GWh) -- nearly 20% of the total electricity generation mix. June 2025 was a milestone month: Solar became the EU's single largest electricity source for the first time ever. It supplied 22% of all power that month, edging out nuclear (21.6%), wind (15.8%), hydro (14.1%), and natural gas (13.8%). [...] In total, 15 EU countries saw their share of renewable generation rise year-over-year. Luxembourg (+13.5 percentage points) and Belgium (+9.1 pp) posted the most significant gains, driven largely by solar power growth. Across the EU, solar made up 36.8% of renewable generation, followed by wind at 29.5%, hydro at 26%, biomass at 7.3%, and geothermal at 0.4%.

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Researchers have unveiled two new hardware-based attacks, Battering RAM and Wiretap, that break Intel SGX and AMD SEV-SNP trusted enclaves by exploiting deterministic encryption and physical interposers. Ars Technica reports: In the age of cloud computing, protections baked into chips from Intel, AMD, and others are essential for ensuring confidential data and sensitive operations can't be viewed or manipulated by attackers who manage to compromise servers running inside a data center. In many cases, these protections -- which work by storing certain data and processes inside encrypted enclaves known as TEEs (Trusted Execution Enclaves) -- are essential for safeguarding secrets stored in the cloud by the likes of Signal Messenger and WhatsApp. All major cloud providers recommend that customers use it. Intel calls its protection SGX, and AMD has named it SEV-SNP. Over the years, researchers have repeatedly broken the security and privacy promises that Intel and AMD have made about their respective protections. On Tuesday, researchers independently published two papers laying out separate attacks that further demonstrate the limitations of SGX and SEV-SNP. One attack, dubbed Battering RAM, defeats both protections and allows attackers to not only view encrypted data but also to actively manipulate it to introduce software backdoors or to corrupt data. A separate attack known as Wiretap is able to passively decrypt sensitive data protected by SGX and remain invisible at all times.

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