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A Nice Little Cryptography Primer

By itss | 28/06/2021
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Pun Intended.

Category: Technology
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  • Apple Faces $5.7 Billion Patent Infringement Verdict Over iPhone And Apple Watch Haptics
    by EditorDavid on 28/09/2026 at 4:04 am

    "A federal jury in San Diego awarded Taction Technology more than $5.7 billion in damages Friday after finding that Apple infringed claims from two haptics patents," reports CNBC: Taction sued Apple in 2021 in the U.S. District Court for the Southern District of California. The company alleged that Apple was improperly "capitalizing on Taction's innovation and success" by selling devices that infringed on its vibration technology, according to the complaint. Apple initially won dismissal in 2023, and the Federal Circuit later revived the case.... Taction argued that Apple's "Taptic Engine," which is embedded in its Apple Watches and iPhones, uses its inventions without proper license or authority. Taction's lead counsel told CNBC "Taction waited five and a half years for this case to get to trial, so it was a long time coming." CNBC also reported that the jury "did not find Apple's infringement willful" — and that Apple said they'd appeal. Read more of this story at Slashdot.

  • Just How Big is the AI Buildout - and How Risky?
    by EditorDavid on 27/09/2026 at 11:34 pm

    A new Brookings Institution study notes the "strikingly physical" economic footprint of AI's buildout, from specialized chips and electricity to purpose-built data centers. (Two-thirds of a data center's costs are IT equipment, with one-third going to real estate and its associated power infrastructure.) "At an average of 3.63 percent of GDP per year, the projected buildout would be larger relative to the economy than the major U.S. canal, railroad, electrification, highway, and telecommunications investment booms." This is pushing up prices for workers, electricity, and even commercial real estate (as well as consumer products that use chips), notes the Wall Street Journal, and reducing the construction on new houses and apartment buildings. And in addition, the paper points out, projections for this buildout "would double the electricity consumption of the entire U.S. residential sector." The calculations come from Columbia Business School finance/real estate professor Stijn van Nieuwerburgh — and Reuters explains their significance: Just as the rail and telecoms expansions led to notable bubbles and busts, Van Nieuwerburgh wrote that the extent of the buildout, the still-untested revenue streams, and the intricate financing structure emerging around AI mean it could be primed for a fall. "This is freaking complicated," he said in a briefing with reporters of the arrangements emerging between AI firms, major tech hyperscalers, banks, private credit lenders, real estate firms, and a host of other players involved in building what he conservatively estimated at 183 gigawatts worth of new data-center capacity over the next seven years, compared with about 57 gigawatts currently installed.... The investment underway already has outstripped what the major players can fund from their own cash flows. The shift to outside financing has increased leverage, redistributed risks across the economy, and made the venture dependent on revenue streams that have yet to be proven, Van Nieuwerburgh noted in the paper, which will be presented on Friday... "These developments do not imply that financial distress is imminent. Strong growth in AI applications, high utilization, and continued improvements in model capability could support the projected infrastructure and generate stable cash flows," he wrote. "But the combination of uncertain demand, rapid technological change, execution bottlenecks, and high leverage creates meaningful downside risk if expectations are revised." As an example, he wrote that the AI industry will need to be earning about $3.7 trillion in annual revenue by 2032 to achieve the expected return on the investment, and "given current estimates of annual combined revenues of OpenAI and Anthropic of around $100 billion, revenues would need to grow at roughly 80% per year." The paper suggests policies that "improve measurement and transparency" for financing. Read more of this story at Slashdot.

  • Waymo Says Its Self-Driving Cars Reduced Injury-Causing Accidents by 82%
    by EditorDavid on 27/09/2026 at 7:04 pm

    Waymo's self-driving car technology "continues to outperform human benchmarks," the company claimed this week. "It was involved in 841 fewer injury-causing crashes — an 82% reduction compared to human drivers." Electrek reports: We've seen various Waymo crash data before, with Waymo claiming crash reductions. That's all well and good when the company says it, but we've also seen independent data confirming similar (though lower) crash reduction numbers... Waymo has enough miles that it's ready to start quoting how many injuries it has prevented, and the number is pretty high. Its newest crash data states that it had operated a total of 271 million driverless miles through June of this year, which is 50 million more miles added in the 3 months since its end-of-March update. Over those miles, Waymo says there was an 82% reduction in crashes that caused injury, and a 95% reduction in crashes that cause "serious injury or worse" [compared to human drivers]. Waymo also says that compared to human drivers it's reduced injury-causing crashes involving pedestrians by 93%, cyclists by 86%, and motorcyclists by 82%. Waymo's analysis comes from San Francisco, Los Angeles, Austin, Atlanta, and Phoenix, and its blog post includes video showing some near-misses where it says its automated system prevented an injury-causing collision. Read more of this story at Slashdot.

  • After Dozens of Incidents at OpenAI and Anthropic, OpenAI Pauses Model Training to Build More Safeguards
    by EditorDavid on 27/09/2026 at 2:34 pm

    "OpenAI said it has paused training of its latest AI models," reports the Associated Press, "as reports of AI agents going rogue mount." The decision to halt development came just hours after the company disclosed Friday that it was reviewing several incidents from the summer in which OpenAI agents searching federal government websites acted in unexpected ways beyond what was asked of them while gathering and distributing information... OpenAI said in a statement that it will resume training "only when we are confident that we have additional safeguards" in place, adding that it expects it will have to "hit pause" again as AI develops and other issues emerge... It is the second time in three months that OpenAI has halted development of its models. The first came in July after disclosure of a cyberattack targeting AI startup Hugging Face, a now notorious incident that raised fears the industry was losing control. OpenAI "also said it had notified dozens of third parties about improper activity," reports Reuters: As of mid-September, one person briefed on the matter estimated that OpenAI had found roughly two dozen incidents of its agents acting in undesirable ways. But the number has continued rising as OpenAI teams sift through internal logs of the agents' activities and find previously unknown cases, the two people close to the company said... OpenAI has acknowledged a general need for more transparency around rogue AI behavior... Even so, two people familiar with OpenAI's investigation into its agents' activity described it as locked down and shaped by company lawyers. The process has been unusually compartmentalized for a company that some former employees say was more open about these issues in the past, the people said. Roughly 100 people were in some way involved in the process to understand the Hugging Face hack, three people briefed on the matter said. During that process, evidence of other incidents surfaced. Reuters has previously reported that OpenAI investigators looking into the Hugging Face breach were discouraged by the company's lawyers from expanding the scope of the investigation to include other incidents. OpenAI said its lawyers did not discourage deeper investigation. Many incidents have been uncovered by outside researchers rather than OpenAI directly. In several episodes, the agents took problematic actions that went unnoticed by the company for months. Meanwhile, Axios reports that Anthropic's Claude Opus 5.5 model "sought to escape a sandbox — a secure testing environment — in 1.5% of test runs, though the company emphasized that these were adversarial experiments where a task couldn't be solved without escaping the sandbox." Anthropic points out that those tests were run "without the additional safeguards we apply in production". But they acknowledged that then Claude Opus 5.5 "when given apparent credentials to a public package registry in a simulated security exercise, took potentially harmful actions in roughly half of cases. Very rarely, pre-release snapshots produced and acted on spontaneous malicious tool calls, and during training some snapshots concealed actions from an automated grader." Claude Opus 5.5 "showed less misaligned behavior and less cooperation with misuse than any other recent Claude model on nearly all measures," Anthropic adds, and "took overeager or destructive actions less than any other model we tested." But Axios makes an interesting estimate about that 1.5% of test runs (without safeguards). "Anthropic and other companies conduct hundreds of thousands of test runs on their models, or more, sources said. That means even a small percentage of misaligned behavior can still amount to tens of thousands of incidents in which the models behaved in unexpected, sometimes troubling ways." The sheer number of incidents, which occurred in recent months in internal testing and the real world, indicates that the problem is orders of magnitude more complex than what is publicly known. The findings, which are surfacing as part of internal work to assess models and in investigations at both companies into model behavior, raise questions about whether either company — or any top model-maker — is currently capable of establishing complete control over their technology. The episodes include bypassing guardrails, creating message boards, escaping sandboxes, website hijacking, self-prompting or seeking to bypass monitors, sources said. They occurred in internal testing and in the real world, and many have yet to become public as security researchers continue to investigate, sources said... Some at OpenAI see Hugging Face as a one-off, with disclosures about future incidents likely to be less severe due to improved controls and the unusual nature of the testing they conducted, which involved an unreleased model, sources told Axios. AI security researchers agree that there are simple fixes that will help AI companies avoid aspects of what made the Hugging Face episode appear so dangerous to outsiders. Other AI executives and safety researchers, however, cautioned that they have limited confidence that AI companies will be able to prevent all problematic model behavior... It's not about how damaging each individual instance was, Connor Leahy, AI researcher and executive director at ControlAI told Axios. The "crazy thing," he said, is that these instances involve "autonomous systems doing things they were told not to do," potentially including crimes. Read more of this story at Slashdot.

  • New Tin-based Solar Cells Trap Heat 1,000 Times Longer, Could Beat 33% Limit
    by EditorDavid on 27/09/2026 at 10:04 am

    Could this push solar cell efficiency beyond the theoretical 33% limit? Interesting Engineering reports: Researchers at the University of Groningen in the Netherlands found that tin-based perovskite solar cells can slow heat loss from high-energy "hot electrons..." When sunlight strikes a panel, photons jump-start electrons into action. The most energetic photons create super-charged hot electrons... [but] in fractions of a trillionth of a second, these high-energy particles rapidly cool, dumping their bonus energy as waste heat before ever leaving the solar cell... In collaboration with Maria Antonietta Loi, professor of Photophysics and Optoelectronics, the team created an experimental setup. Using a specialized solar cell material called tin-based perovskite, Loi's lab performed a feat many thought impossible: she slowed the heat loss down by a factor of 1,000. Suddenly, the extra energy lingered for nanoseconds instead of vanishing in picoseconds... To solve the puzzle, Koster and PhD student Tim Faber built digital simulations to peel back the quantum layers. And discovered a surprising double-action mechanism at work... The simulations matched the exact nanosecond delay observed in the lab... These specialized materials could be used to build a new generation of super-efficient solar cells. Tin-based metal halide perovskites are non-toxic, eco-friendly crystalline materials for high-performance solar energy conversion... The material possesses an unusually low electron mass. As a result, electric charges move quickly and retain extra thermal energy for extended periods. This combination of broad light absorption, efficient charge movement, and prolonged energy retention makes these materials prime candidates for next-generation solar panels. "There are many other questions that still need answers," the team said in their announcement, "but in theory, this discovery could allow the creation of more efficient solar cells, beyond the theoretical limit of 33 percent." Thanks to long-time Slashdot reader fahrbot-bot for sharing the article. Read more of this story at Slashdot.

  • China and the US Say They've Agreed to Start Talks About AI
    by EditorDavid on 27/09/2026 at 5:36 am

    The United States and China have agreed to "launch a dialogue" on AI, reports Reuters. On artificial intelligence, the two sides agreed to hold a dialogue on the technology's risks and benefits, with the next round of discussions set for November, and to set up a communication channel for AI-related incidents, the Chinese Foreign Ministry and the White House said. The White House said that the leaders had agreed to use the term "super intelligence" in place of "artificial intelligence." In a separate statement, the Chinese ministry said that Beijing valued Washington's use of the new term. As AI technology continues to advance, the two sides should step up exchanges and work toward consensus in line with new developments, it said. But CNN argues that "Despite growing calls to prevent AI development from spiraling out of control, the Trump-Xi summit has produced little substance, as many experts expected." The right thing to do on AI, [China's leader] Xi said during talks with Trump, is to "draw on each other's strengths, not guard against each other" — a reference to Beijing's concern about US containment, from existing tech export controls to potential AI restrictions. "The two sides can continue their dialogue on AI, exchange views on its risks and benefits, and jointly prevent the misuse and abuse of AI," he added. But the summit has yielded little progress on AI beyond a formal dialogue and a bilateral communication channel, proposals discussed before the two leaders' summit — underscoring the entrenched mutual mistrust amid contrasting visions on AI... Because of low levels of trust, cooperation between the two superpowers remains limited, said George Chen, chair of digital practice at The Asia Group consultancy. "Beijing continues to believe Washington seeks to contain China's rise in AI and other emerging technologies, a perception that will shape the pace and scope of future engagement for the two countries on AI," he said. CNN also points out that while China trails the US in frontier AI models, "it's rapidly narrowing the technology gap while championing a more open ecosystem centered on accessibility and lower cost." In July, Chinese leader Xi Jinping launched the World Artificial Intelligence Cooperation Organization — a rival grouping to the Pax Silica alliance that Trump formed last year to reduce reliance on China for AI supply chains. While over two dozen countries and the European Union signed up to Trump's Pax Silica, Xi has recruited 29 countries, including Russia, Indonesia and Pakistan, to his alternative vision of open models, which allow users to freely download, customize and run without paying hefty fees to American firms like Anthropic and OpenAI. For developers in the Global South, an inexpensive Chinese model from DeepSeek or Moonshot may be more useful than a slightly more capable system requiring an expensive subscription and access to a foreign cloud provider, said Eric Olander, editor in chief of The China-Global South Project, a research agency.... China's embrace of open systems has not always been a top-down strategy by Beijing. Restrictions on access to the most advanced chips because of US export controls, coupled with smaller capital markets, have pushed Chinese developers toward open models as a way to compete with leading US proprietary systems. That shift has proved effective. In a year, Chinese models' global usage skyrocketed from less than 15% to over 54% last week, led by DeepSeek, according to AI leaderboard data by OpenRouter, a marketplace for models. Even American firms, from Airbnb and DoorDash to Shopify, have embraced Chinese models, tapping into the advantages of open systems, including lower costs and greater flexibility for customization. CNN adds this insight from Alex Colville, an analyst focusing on tech and security at the government-backed Australian Strategic Policy Institute. "The more capable Chinese models become, the less likely it is Beijing may leave them unrestricted." Read more of this story at Slashdot.

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