Protected KVM (pKVM), the hypervisor powering the Android Virtualization Framework, has officially achieved SESIP Level 5 certification (in testing by cybersecurity lab Dekra against the TrustCB SESIP scheme).

Google's security blog called the certification "a watershed moment," and a "new benchmark" for both open-source security — and for the future of consumer electronics. "It provides a single, open-source, and exceptionally high-quality firmware base that all device manufacturers can build upon." This makes pKVM the first software security system designed for large-scale deployment in consumer electronics to meet this assurance bar. The implications for the future of secure mobile technology are profound. With this level of security assurance, Android is now positioned to securely support the next generation of high-criticality isolated workloads. This includes vital features, such as on-device AI workloads that can operate on ultra-personalized data, with the highest assurances of privacy and integrity...

Achieving Security Evaluation Standard for IoT Platforms (SESIP) Level 5 is a landmark because it incorporates AVA_VAN.5, the highest level of vulnerability analysis and penetration testing under the ISO 15408 (Common Criteria) standard. A system certified to this level has been evaluated to be resistant to highly skilled, knowledgeable, well-motivated, and well-funded attackers who may have insider knowledge and access. This certification is the cornerstone of the next-generation of Android's multi-layered security strategy. Many of the TEEs (Trusted Execution Environments) used in the industry have not been formally certified or have only achieved lower levels of security assurance... Looking ahead, Android device manufacturers will be required to use isolation technology that meets this same level of security for various security operations that the device relies on. Protected KVM ensures that every user can benefit from a consistent, transparent, and verifiably secure foundation.
"This achievement represents just one important aspect of the immense, multi-year dedication from the Linux and KVM developer communities and multiple engineering teams at Google developing pKVM and AVF," the post concludes.

"We look forward to seeing the open-source community and Android ecosystem continue to build on this foundation, delivering a new era of high-assurance mobile technology for users."

Duolingo's stock peaked at $529.05 on May 16th. Three months later, it's down 38% — with that drop starting shortly after backlash to the CEO's promise to make it an "AI-first" company.

Yet "The backlash against Duolingo going 'AI-first' didn't even matter," TechCrunch wrote August 7th, noting Duolingo's stock price surged almost 30% overnight. That surge vanished within two days — and instead of a 30% surge, Duolingo now shows a 5% drop over the last eight days.

Yahoo Finance blames the turnaround on OpenAI's GPT-5 demo, "which demonstrated, among many other things, its ability to create a language-learning tool from a short prompt." OpenAI researcher Yann Dubois asked the model to create an app to help his partner learn French. And in a few minutes GPT-5 churned out several iterations, with flashcards, a progress tracker, and even a simple snake-style game with a French twist, a mouse and cheese variation to learn new vocab....

[Duolingo's] corporate lawyers, of course, did warn against this in its annual 10-K, albeit in boilerplate language. Tucked into the risk factors section, Duolingo notes, "It is possible that a new product could gain rapid scale at the expense of existing brands through harnessing a new technology (such as generative AI)." Consider this another warning to anyone making software. [The article adds later that "Rapid development and fierce competition can leave firms suddenly behind — perceived as under threat, inferior, or obsolete — from every iteration of OpenAI's models and from the moves of other influential AI players..."]

There's also irony in the wild swings. Part of Duolingo's successful quarter stemmed from the business's efficient use of AI. Gross margins, the company said, outperformed management expectations due to lower AI costs. And AI conversational features have become part of the company's learning tools, helping achieve double-digit subscriber growth... But the enthusiasm for AI, which led to the initial stock bump this week, also led to the clawback. AI giveth and taketh away.
Meanwhile, this week a blog announced it was "able to activate a long-rumored Practice feature" hidden in Google Translate, notes PC Magazine, with the blogger even sharing a screen recording of "AI-led features within Translate" showing its ability to create personalized lessons. "Google's take on Duolingo is effectively ready for release," the Android Authority blog concluded. "Furthermore, the fact that a Telegram user spotted this in their app suggests that Google is already testing this in a limited fashion."

Duolingo's CEO revisited the backlash to his original "AI-first" promise today in a new interview today with the New York Times, emphasizing his hope that AI would only reduce the company's use of contractors. "We've never laid off any full-time employees. We don't plan to...." But: In the next five years, people's jobs will probably change. We're seeing it with many of our engineers. They may not be doing some rote tasks anymore. What will probably happen is that one person will be able to accomplish more, rather than having fewer people.

NYT: How are you managing that transition for employees?

Every Friday morning, we have this thing: It's a bad acronym, f-r-A-I-days. I don't know how to pronounce it. Those mornings, we let each team experiment on how to get more efficient to use A.I.
Yesterday there was also a new announcement from attorneys at Pomerantz LLP, which calls itself "the oldest law firm in the world dedicated to representing the rights of defrauded investors."

The firm announced it was investigating "whether Duolingo and certain of its officers and/or directors have engaged in securities fraud or other unlawful business practices."

Matt Asay answered questions from Slashdot readers in 2010 as the then-COO of Canonical. Today he runs developer marketing at Oracle (after holding similar positions at AWS, Adobe, and MongoDB).

And this week Asay contributed an opinion piece to InfoWorld reminding us of open source contributions from companies where "enlightened self-interest underwrites the boring but vital work — CI hardware, security audits, long-term maintenance — that grassroots volunteers struggle to fund." [I]f you look at the Linux 6.15 kernel contributor list (as just one example), the top contributor, as measured by change sets, is Intel... Another example: Take the last year of contributions to Kubernetes. Google (of course), Red Hat, Microsoft, VMware, and AWS all headline the list. Not because it's sexy, but because they make billions of dollars selling Kubernetes services... Some companies (including mine) sell proprietary software, and so it's easy to mentally bucket these vendors with license fees or closed cloud services. That bias makes it easy to ignore empirical contribution data, which indicates open source contributions on a grand scale.
Asay notes Oracle's many contributions to Linux: In the [Linux kernel] 6.1 release cycle, Oracle emerged as the top contributor by lines of code changed across the entire kernel... [I]t's Oracle that patches memory-management structures and shepherds block-device drivers for the Linux we all use. Oracle's kernel work isn't a one-off either. A few releases earlier, the company topped the "core of the kernel" leaderboard in 5.18, and it hasn't slowed down since, helping land the Maple Tree data structure and other performance boosters. Those patches power Oracle Cloud Infrastructure (OCI), of course, but they also speed up Ubuntu on your old ThinkPad. Self-interested contributions? Absolutely. Public benefit? Equally absolute.

This isn't just an Oracle thing. When we widen the lens beyond Oracle, the pattern holds. In 2023, I wrote about Amazon's "quiet open source revolution," showing how AWS was suddenly everywhere in GitHub commit logs despite the company's earlier reticence. (Disclosure: I used to run AWS' open source strategy and marketing team.) Back in 2017, I argued that cloud vendors were open sourcing code as on-ramps to proprietary services rather than end-products. Both observations remain true, but they miss a larger point: Motives aside, the code flows and the community benefits.

If you care about outcomes, the motives don't really matter. Or maybe they do: It's far more sustainable to have companies contributing because it helps them deliver revenue than to contribute out of charity. The former is durable; the latter is not.
There's another practical consideration: scale. "Large vendors wield resources that community projects can't match."

Asay closes by urging readers to "Follow the commits" and "embrace mixed motives... the point isn't sainthood; it's sustainable, shared innovation. Every company (and really every developer) contributes out of some form of self-interest. That's the rule, not the exception. Embrace it." Going forward, we should expect to see even more counterintuitive contributor lists. Generative AI is turbocharging code generation, but someone still has to integrate those patches, write tests, and shepherd them upstream. The companies with the most to lose from brittle infrastructure — cloud providers, database vendors, silicon makers — will foot the bill. If history is a guide, they'll do so quietly.

Last month, Python "reached the highest ranking a programming language ever had in the TIOBE index," according to TIOBE CEO Paul Jansen.

"We thought Python couldn't grow any further, but AI code assistants let Python take yet another step forward." According to recent studies of Stanford University (Yegor Denisov-Blanch), AI code assistants such as Microsoft Copilot, Cursor or Google Gemini Code Assist are 20% more effective if used for popular programming languages. The reason for this is obvious: there is more code for these languages available to train the underlying models. This trend is visible in the TIOBE index as well, where we see a consolidation of languages at the top. Why would you start to learn a new obscure language for which no AI assistance is available? This is the modern way of saying that you don't want to learn a new language that is hardly documented and/or has too few libraries that can help you.
TIOBE's "Programming Community Index" attempts to calculate the popularity of languages using the number of skilled engineers, courses, and third-party vendors. It nows gives Python a 26.14% rating, which TechRepublic notes "is well ahead of the next two programming languages on this month's leaderboard: C++ is at 9.18% and C is 9.03%." But the first top six languages haven't changed since last year...

1. Python
2. C++
3. C
4. Java
5. C#
6. JavaScript

Since August of 2024 SQL has dropped from its #7 rank down to #12 (meaning Visual Basic and Go each rise up one rank from their position a year ago, into the #7 and #8 positions).

In the last year Perl has risen from the #25 position to #9, beating out Delphi/Oracle Pascal at #10, and Fortran at #11 (last year's #10). TIOBE CEO Jansen "told TechRepublic in an email that many people were asking why Perl was becoming more popular, but he didn't have a definitive answer. He said he double-checked the underlying data and found the increase to be accurate, though the reason for the shift remains unclear."

New data from Digital Content Next shows Google's AI Overviews are linked to notable drops in publisher referral traffic, with surveyed sites seeing year-over-year declines between 1% and 25%. From a report: Digital Content Next (DCN), which counts the New York Times, Conde Nast and Vox among its approximately 40 member companies, checked in with 19 of them between May and June to see what was happening to their Google search referral traffic. The upshot: Google AI Overviews is indeed harming publisher traffic. Organic search referral traffic from Google is declining broadly, with the majority of DCN member sites -- spanning both news and entertainment -- experiencing traffic losses from Google search between 1% and 25%. Twelve of the respondent companies were news brands, and seven were non-news.

Over eight weeks in May and June 2025, the median Google Search referral was down almost every week, with losses outpacing gains two-to-one. For the seven non-news brands in the survey, the downward slope was steady and unbroken. Across the eight weeks, the median YoY decline in referred traffic from Google Search was -10% overall, -7% for news brands, and -14% for non-news brands, per the results.

Jason Kint, CEO of DCN, stressed that these losses are a direct consequence of Google AI Overviews, as many publishers claimed in their responses. The latest data offers a "ground truth" of what's actually happening, cutting through Google's vague claims about "quality clicks," made in its latest post, he added. "I think all publishers are ignoring Google's post. But this probably helps ground that," added Kint. The findings come shortly after a recent Pew survey of 900 U.S. consumers found that AI summaries are making users less likely to click through to links. The U.K.'s Professional Publishers Association (PPA) also found that AI Overviews and AI Mode are steering users toward zero-click results, reducing visits to source sites, and expanding into Google Discover where sources are relegated to citations. Evidence from members shows click-through rates falling 10-25% year-over-year despite stable rankings, with examples including a lifestyle publisher's CTR dropping from 5.1% to 0.6% and an automotive publisher's CTR falling from 2.75% to 1.71% despite increased visibility.

The African Union has endorsed the "Correct The Map" campaign, urging governments and global institutions to replace the distorted 16th-century Mercator projection with the Equal Earth map that more accurately represents Africa's true size. Reuters reports: "It might seem to be just a map, but in reality, it is not," AU Commission deputy chairperson Selma Malika Haddadi told Reuters, saying the Mercator fostered a false impression that Africa was "marginal," despite being the world's second-largest continent by area, with 54 nations and over a billion people. Such stereotypes influence media, education and policy, she said. Criticism of the Mercator map is not new, but the 'Correct The Map' campaign led by advocacy groups Africa No Filter and Speak Up Africa has revived the debate, urging organizations to adopt the 2018 Equal Earth projection, which tries to reflect countries' true sizes.

"The current size of the map of Africa is wrong," Moky Makura, executive director of Africa No Filter, said. "It's the world's longest misinformation and disinformation campaign, and it just simply has to stop." Fara Ndiaye, co-founder of Speak Up Africa, said the Mercator affected Africans' identity and pride, especially children who might encounter it early in school. "We're actively working on promoting a curriculum where the Equal Earth projection will be the main standard across all (African) classrooms," Ndiaye said, adding she hoped it would also be the one used by global institutions, including Africa-based ones. [...]

The Mercator projection is still widely used, including by schools and tech companies. Google Maps switched from Mercator on desktop to a 3D globe view in 2018, though users can still switch back to the Mercator if they prefer. On the mobile app, however, the Mercator projection remains the default. 'Correct The Map' wants organizations like the World Bank and the United Nations to adopt the Equal Earth map. A World Bank spokesperson said they already use the Winkel-Tripel or Equal Earth for static maps and are phasing out Mercator on web maps.

An anonymous reader quotes a report from Ars Technica: Google has announced a tiny version of its Gemma open model designed to run on local devices. Google says the new Gemma 3 270M can be tuned in a snap and maintains robust performance despite its small footprint. [...] Running an AI model locally has numerous benefits, including enhanced privacy and lower latency. Gemma 3 270M was designed with these kinds of use cases in mind. In testing with a Pixel 9 Pro, the new Gemma was able to run 25 conversations on the Tensor G4 chip and use just 0.75 percent of the device's battery. That makes it by far the most efficient Gemma model.

Developers shouldn't expect the same performance level of a multi-billion-parameter model, but Gemma 3 270M has its uses. Google used the IFEval benchmark, which tests a model's ability to follow instructions, to show that its new model punches above its weight. Gemma 3 270M hits a score of 51.2 percent in this test, which is higher than other lightweight models that have more parameters. The new Gemma falls predictably short of 1 billion-plus models like Llama 3.2, but it gets closer than you might think for having just a fraction of the parameters.

Google claims Gemma 3 270M is good at following instructions out of the box, but it expects developers to fine-tune the model for their specific use cases. Due to the small parameter count, that process is fast and low-cost, too. Google sees the new Gemma being used for tasks like text classification and data analysis, which it can accomplish quickly and without heavy computing requirements. You can download the new Gemma for free, and the model weights are available. There's no separate commercial licensing agreement, so developers can modify, publish, and deploy Gemma 3 270M derivatives in their tools. You can download Gemma 3 270M from Hugging Face and Kaggle in both pre-trained and instruction-tuned versions.

Electricity rates for individuals and small businesses could rise sharply as Amazon, Google, Microsoft and other technology companies build data centers and expand into the energy business. Residential electricity bills increased at least $15 monthly for Ohio households starting in June due to data center demands, according to utility data and an independent grid monitor. A Carnegie Mellon University and North Carolina State University analysis projects average U.S. electricity bills will rise 8% by 2030 from data center growth, with Virginia facing potential 25% increases. Virginia regulators estimate residents could pay an additional $276 annually by 2030.

National residential electricity rates have already risen more than 30% since 2020. Tech companies' AI push requires data centers that consumed over 4% of U.S. electricity in 2023, with government analysts projecting consumption reaching 12% within three years. American Electric Power warned Ohio regulators that without new rate structures requiring data centers to pay more upfront costs, residents and small businesses would bear much of the expense for grid upgrades.

Igor Babuschkin, co-founder of xAI, has left the company to start Babuschkin Ventures, a VC firm focused on AI safety and humanity-advancing startups. TechCrunch reports: Babuschkin led engineering teams at xAI and helped build the startup into one of Silicon Valley's leading AI model developers just a few years after it was founded. "Today was my last day at xAI, the company that I helped start with Elon Musk in 2023," Babuschkin wrote in the post. "I still remember the day I first met Elon, we talked for hours about AI and what the future might hold. We both felt that a new AI company with a different kind of mission was needed."

Babuschkin is leaving xAI to launch his own venture capital firm, Babuschkin Ventures, which he says will support AI safety research and back startups that "advance humanity and unlock the mysteries of our universe." The xAI co-founder says he was inspired to start the firm after a dinner with Max Tegmark, the founder of the Future of Life Institute, in which they discussed how AI systems could be built safely to encourage the flourishing of future generations. In his post, Babuschkin says his parents immigrated to the U.S. from Russia in pursuit of a better life for their children.

Prior to co-founding xAI, Babuschkin was part of a research team at Google DeepMind that pioneered AlphaStar in 2019, a breakthrough AI system that could defeat top-ranked players at the video game StarCraft. Babuschkin also worked as a researcher at OpenAI in the years before it released ChatGPT. In his post, Babuschkin details some of the challenges he and Musk faced in building up xAI. He notes that industry veterans called xAI's goal of building its Memphis, Tennessee supercomputer in just three months "impossible." [...] Nevertheless, Babuschkin says he's already looking back fondly on his time at xAI, and "feels like a proud parent, driving away after sending their kid away to college." "I learned 2 priceless lessons from Elon: #1 be fearless in rolling up your sleeves to personally dig into technical problems, #2 have a maniacal sense of urgency," said Babuschkin.

Data brokers are required by California law to provide ways for consumers to request their data be deleted. But good luck finding them. From a report: More than 30 of the companies, which collect and sell consumers' personal information, hid their deletion instructions from Google, according to a review by The Markup and CalMatters of hundreds of broker websites. This creates one more obstacle for consumers who want to delete their data.

Many of the pages containing the instructions, listed in an official state registry, use code to tell search engines to remove the page entirely from search results. Popular tools like Google and Bing respect the code by excluding pages when responding to users. Data brokers nationwide must register in California under the state's Consumer Privacy Act, which allows Californians to request that their information be removed, that it not be sold, or that they get access to it. After reviewing the websites of all 499 data brokers registered with the state, we found 35 had code to stop certain pages from showing up in searches.

An anonymous reader quotes a report from The Verge: Google is rolling out an update for Gemini that will allow the AI chatbot to "remember" your past conversations without prompting. With the setting turned on, Gemini will automatically recall your "key details and preferences" and use them to personalize its output.

This expands upon an update that Google introduced last year, which lets you ask Gemini to "remember" your personal preferences and interests. Now, Gemini won't need prompting to recall this information. As an example, Google says if you've used Gemini to get ideas for a YouTube channel surrounding Japanese culture in the past, then AI chatbot might suggest creating content about trying Japanese food if you ask it to suggest new video ideas in the future. [...]

Google will turn on this feature by default, but you can disable it by heading to your settings in the Gemini app and selecting Personal Context. From there, toggle off the Your past chats with Gemini option. Google will roll out this feature to its Gemini 2.5 Pro model in "select countries" starting today, before eventually bringing it to more locations and its Gemini 2.5 Flash model. Google will also rename its "Gemini Apps Activity" setting to "Keep Activity," which will use "a sample" of your file and photo uploads to Gemini to "help improve Google services for everyone" starting on September 2nd. If you've disabled the previous setting, the new "Keep Activity" setting will be disabled too.

There's also a new "temporary chats" feature in Gemini to preserve privacy. "Temporary chats won't appear in your recent chats or your Keep Activity setting," notes The Verge. "Gemini also won't use these chats to personalize future conversations, nor will Google use them to train its AI models. Google will only save these conversations for 72 hours."

IBM and Google report they will build industrial-scale quantum computers containing one million or more qubits by 2030, following IBM's June publication of a quantum computer blueprint addressing previous design gaps and Google's late-2023 breakthrough in scaling error correction.

Current experimental systems contain fewer than 200 qubits. IBM encountered crosstalk interference when scaling its Condor chip to 433 qubits and subsequently adopted low-density parity-check code requiring 90% fewer qubits than Google's surface code method, though this requires longer connections between distant qubits.

Google plans to reduce component costs tenfold to achieve its $1 billion target price for a full-scale machine. Amazon Web Services quantum hardware executive Oskar Painter told FT he estimates useful quantum computers remain 15-30 years away, citing engineering challenges in scaling despite resolved fundamental physics problems.

Google, Cisco, and McKinsey have reintroduced in-person interviews to combat AI-assisted cheating in virtual technical assessments. Coda Search/Staffing reports client requests for face-to-face meetings has surged to 30% this year from 5% in 2024.

A Gartner survey of 3,000 job seekers found 6% admitted to interview fraud including having someone else stand in for them, while the FBI has warned of thousands of North Korean nationals using false identities to secure remote positions at U.S. technology companies. Google CEO Sundar Pichai confirmed in June the company now requires at least one in-person round for certain roles to verify candidates possess genuine coding skills.

Google is rolling out a new feature called "Preferred Sources" in the U.S. and India, which allows users to select their preferred choice of news sites and blogs to be shown in the Top Stories section of Google's search results. From a report: Enabling this feature means you will see more content from the sites you like, the company says. When users search for a particular topic, they will see a "star" icon next to the Top Stories section. They can tap on that icon and start adding sources by searching for them. Once you select the sources, you can refresh the results to see more content from your selected sources. Google said that for some queries, users will also see a separate "From your sources" section below the Top Stories section.

Australia's Federal Court ruled Tuesday that Apple and Google violated competition law through anti-competitive app store practices. Judge Jonathan Beach found both companies breached section 46 of the Competition and Consumer Act by misusing market power to reduce competition.

The decision covers class actions representing 15 million consumers and 150,000 developers seeking compensation for inflated prices from 2017-2022, plus separate Epic Games cases. Apple's exclusive iOS App Store and mandatory payment system, along with Google's Play Store billing requirements, were ruled anti-competitive despite security justifications. Compensation amounts will be determined at subsequent hearings, with estimates reaching hundreds of millions of dollars.

AI startup Perplexity on Tuesday offered to purchase Google's Chrome browser for $34.5 billion as it works to challenge the tech giant's web-search dominance. From a report: Perplexity's offer is significantly more than its own valuation, which is estimated at $18 billion. The company told The Wall Street Journal that several investors including large venture-capital funds had agreed to back the transaction in full.

Estimates of Chrome's enterprise value vary widely but recent ones have ranged from $20 billion to $50 billion. U.S. District Judge Amit Mehta is weighing whether to force Google to sell the browser as a means of weakening Google's stranglehold on web search. Mehta last year ruled that Google illegally monopolized the search market and is expected to rule this month on how to restore competition.

An anonymous reader quotes a report from Ars Technica: In recent months, the AI industry has started moving toward so-called simulated reasoning models that use a "chain of thought" process to work through tricky problems in multiple logical steps. At the same time, recent research has cast doubt on whether those models have even a basic understanding of general logical concepts or an accurate grasp of their own "thought process." Similar research shows that these "reasoning" models can often produce incoherent, logically unsound answers when questions include irrelevant clauses or deviate even slightly from common templates found in their training data.

In a recent pre-print paper, researchers from the University of Arizona summarize this existing work as "suggest[ing] that LLMs are not principled reasoners but rather sophisticated simulators of reasoning-like text." To pull on that thread, the researchers created a carefully controlled LLM environment in an attempt to measure just how well chain-of-thought reasoning works when presented with "out of domain" logical problems that don't match the specific logical patterns found in their training data. The results suggest that the seemingly large performance leaps made by chain-of-thought models are "largely a brittle mirage" that "become[s] fragile and prone to failure even under moderate distribution shifts," the researchers write. "Rather than demonstrating a true understanding of text, CoT reasoning under task transformations appears to reflect a replication of patterns learned during training." [...]

Rather than showing the capability for generalized logical inference, these chain-of-thought models are "a sophisticated form of structured pattern matching" that "degrades significantly" when pushed even slightly outside of its training distribution, the researchers write. Further, the ability of these models to generate "fluent nonsense" creates "a false aura of dependability" that does not stand up to a careful audit. As such, the researchers warn heavily against "equating [chain-of-thought]-style output with human thinking" especially in "high-stakes domains like medicine, finance, or legal analysis." Current tests and benchmarks should prioritize tasks that fall outside of any training set to probe for these kinds of errors, while future models will need to move beyond "surface-level pattern recognition to exhibit deeper inferential competence," they write.

In 2020 a YouTube video used video footage of Steve Wozniak in a scam to steal bitcoin. "Some people said they lost their life savings," Wozniak tells CBS News, explaining why he sued YouTube in 2020 — and where his case stands now: Wozniak's lawsuit against YouTube has been tied up in court now for five years, stalled by federal legislation known as Section 230. Attorney Brian Danitz said, "Section 230 is a very broad statute that limits, if not totally, the ability to bring any kind of case against these social media platforms."

"It says that anything gets posted, they have no liability at all," said Wozniak. "It's totally absolute."

Google responded to our inquiry about Wozniak's lawsuit with a statement from José Castañeda, of Google Policy Communications: "We take abuse of our platform seriously and take action quickly when we detect violations ... we have tools for users to report channels that are impersonating their likeness or business." [Steve's wife] Janet Wozniak, however, says YouTube did nothing, even though she reported the scam video multiple times: "You know, 'Please take this down. This is an obvious mistake. This is fraud. You're YouTube, you're helping dupe people out of their money,'" she said.

"They wouldn't," said Steve...
Today is Steve Wozniak's 75th birthday. (You can watch the interview here.) And the article includes this interesting detail about Woz's life today: Wozniak sold most of his Apple stock in the mid-1980s when he left the company. Today, though, he still gets a small paycheck from Apple for making speeches and representing the company. He says he's proud to see Apple become a trillion-dollar company. "Apple is still the best," he said. "And when Apple does things I don't like, and some of the closeness I wish it were more open, I'll speak out about it. Nobody buys my voice!"

I asked, "Apple listen to you when you speak out?"

"No," Wozniak smiled. "Oh, no. Oh, no."
Wozniak answered questions from Slashdot readers in 2000 and again in 2012.

And he dropped by Slashdot on his birthday to leave this comment for Slashdot's readers...

Last week saw the 80th anniversary of a turning point in World War II: the day America dropped an atomic bomb on Hiroshima.

"Twelve men were on that flight..." remembers the online magazine Mental Floss, adding "Almost all had something to say after the war." The group was segregated from the rest of the military and trained in secret. Even those in the group only knew as much as they needed to know in order to perform their duties. The group deployed to Tinian in 1945 with 15 B-29 bombers, flight crews, ground crews, and other personnel, a total of about 1770 men. The mission to drop the atomic bomb on Hiroshima, Japan (special mission 13) involved seven planes, but the one we remember was the Enola Gay.

Air Force captain Theodore "Dutch" Van Kirk did not know the destructive force of the nuclear bomb before Hiroshima. He was 24 years old at that time, a veteran of 58 missions in North Africa. Paul Tibbets told him this mission would shorten or end the war, but Van Kirk had heard that line before. Hiroshima made him a believer. Van Kirk felt the bombing of Hiroshima was worth the price in that it ended the war before the invasion of Japan, which promised to be devastating to both sides. " I honestly believe the use of the atomic bomb saved lives in the long run. There were a lot of lives saved. Most of the lives saved were Japanese."

In 2005, Van Kirk came as close as he ever got to regret. "I pray no man will have to witness that sight again. Such a terrible waste, such a loss of life..."
Many of the other crewmembers also felt the bomb ultimately saved lives.

The Washington Post has also published a new oral history of the flight after it took off from Tinian Island. The oral history was assembled for a new book published this week titled The Devil Reached Toward the Sky: An Oral History of the Making and Unleashing of the Atomic Bomb.. Col. Paul W. Tibbets, lead pilot of the Enola Gay: We were only eight minutes off the ground when Capt. William S. "Deak" Parsons and Lt. Morris R. Jeppson lowered themselves into the bomb bay to insert a slug of uranium and the conventional explosive charge into the core of the strange-looking weapon. I wondered why we were calling it ''Little Boy." Little Boy was 28 inches in diameter and 12 feet long. Its weight was a little more than 9,000 pounds. With its coat of dull gunmetal paint, it was an ugly monster...

Lt. Morris R. Jeppson, crew member of the Enola Gay: Parsons was second-in-command of the military in the Manhattan Project. The Little Boy weapon was Parsons's design. He was greatly concerned that B-29s loaded with conventional bombs were crashing at the ends of runways on Tinian during takeoff and that such an event could cause the U-235 projectile in the gun of Little Boy to fly down the barrel and into the U-235 target. This could have caused a low-level nuclear explosion on Tinian...

Jeppson: On his own, Parsons decided that he would go on the Hiroshima mission and that he would load the gun after the Enola Gay was well away from Tinian.

Tibbets: That way, if we crashed, we would lose only the airplane and crew, himself included... Jeppson held the flashlight while Parsons struggled with the mechanism of the bomb, inserting the explosive charge that would send one block of uranium flying into the other to set off the instant chain reaction that would create the atomic explosion.
The navigator on one of the other six planes on the mission remember that watching the mushroom cloud, "There was almost complete silence on the flight deck. It was evident the city of Hiroshima was destroyed."

And the Enola Gay's copilot later remembered thinking: "My God, what have we done?"

Imagine this. Lightning sparks a wildfire, but "within seconds, a satellite dish swirling overhead picks up on the anomaly and triggers an alarm," writes the Los Angeles Times. "An autonomous helicopter takes flight and zooms toward the fire, using sensors to locate the blaze and AI to generate a plan of attack. It measures the wind speed and fire movement, communicating constantly with the unmanned helicopter behind it, and the one behind that. Once over the site, it drops a load of water and soon the flames are smoldering. Without deploying a single human, the fire never grows larger than 10 square feet.

"This is the future of firefighting." On a recent morning in San Bernardino, state and local fire experts gathered for a demonstration of the early iterations of this new reality. An autonomous Sikorski Black Hawk helicopter, powered by technology from Lockheed Martin and a California-based software company called Rain, is on display on the tarmac of a logistics airport in Victorville — the word "EXPERIMENTAL" painted on its military green-black door. It's one of many new tools on the front lines of firefighting technology, which experts say is evolving rapidly as private industry and government agencies come face-to-face with a worsening global climate crisis...

Scientific studies and climate research models have found that the number of extreme fires could increase by as much as 30% globally by 2050. By 2100, California alone could see a 50% increase in wildfire frequency and a 77% increase in average annual acres burned, according to the state's most recent climate report. That's largely because human-caused climate change is driving up temperatures and drying out the landscape, priming it to burn, according to Kate Dargan Marquis, a senior advisor with the Gordon and Betty Moore Foundation who served as California's state fire marshal from 2007 to 2010.... "[T]he policies of today and the technologies of today are not going to serve us tomorrow."

Today, more than 1,100 mountaintop cameras positioned across California are already using artificial intelligence to scan the landscape for the first sign of flames and prompt crews to spring into action. NASA's Earth-observing satellites are studying landscape conditions to help better predict fires before they ignite, while a new global satellite constellation recently launched by Google is helping to detect fires faster than ever before.
One 35-year fire service veteran who consults on fire service technologies even predicts fire-fighting robots will also be used in high-risk situations like the Colossus robot that battled flames searing through Notre-Dame Cathedral in Paris...

And a bill moving through California's legislation "would direct the California Department of Forestry and Fire Protection to establish a pilot program to assess the viability of incorporating autonomous firefighting helicopters in the state."