Biz & IT

bank-of-england-warns-ai-stock-bubble-rivals-2000-dotcom-peak

Bank of England warns AI stock bubble rivals 2000 dotcom peak

Share valuations based on past earnings have also reached their highest levels since the dotcom bubble 25 years ago, though the BoE noted they appear less extreme when based on investors’ expectations for future profits. “This, when combined with increasing concentration within market indices, leaves equity markets particularly exposed should expectations around the impact of AI become less optimistic,” the central bank said.

Toil and trouble?

The dotcom bubble offers a potentially instructive parallel to our current era. In the late 1990s, investors poured money into Internet companies based on the promise of a transformed economy, seemingly ignoring whether individual businesses had viable paths to profitability. Between 1995 and March 2000, the Nasdaq index rose 600 percent. When sentiment shifted, the correction was severe: the Nasdaq fell 78 percent from its peak, reaching a low point in October 2002.

Whether we’ll see the same thing or worse if an AI bubble pops is mere speculation at this point. But similarly to the early 2000s, the question about today’s market isn’t necessarily about the utility of AI tools themselves (the Internet was useful, after all, despite the bubble), but whether the amount of money being poured into the companies that sell them is out of proportion with the potential profits those improvements might bring.

We don’t have a crystal ball to determine when such a bubble might pop, or even if it is guaranteed to do so, but we’ll likely continue to see more warning signs ahead if AI-related deals continue to grow larger and larger over time.

Bank of England warns AI stock bubble rivals 2000 dotcom peak Read More »

salesforce-says-it-won’t-pay-extortion-demand-in-1-billion-records-breach

Salesforce says it won’t pay extortion demand in 1 billion records breach

Salesforce says it’s refusing to pay an extortion demand made by a crime syndicate that claims to have stolen roughly 1 billion records from dozens of Salesforce customers.

The threat group making the demands began their campaign in May, when they made voice calls to organizations storing data on the Salesforce platform, Google-owned Mandiant said in June. The English-speaking callers would provide a pretense that necessitated the target connect an attacker-controlled app to their Salesforce portal. Amazingly—but not surprisingly—many of the people who received the calls complied.

It’s becoming a real mess

The threat group behind the campaign is calling itself Scattered LAPSUS$ Hunters, a mashup of three prolific data-extortion actors: Scattered Spider, LAPSuS$, and ShinyHunters. Mandiant, meanwhile, tracks the group as UNC6040, because the researchers so far have been unable to positively identify the connections.

Earlier this month, the group created a website that named Toyota, FedEx, and 37 other Salesforce customers whose data was stolen in the campaign. In all, the number of records recovered, Scattered LAPSUS$ Hunters claimed, was “989.45m/~1B+.” The site called on Salesforce to begin negotiations for a ransom amount “or all your customers [sic] data will be leaked.” The site went on to say: “Nobody else will have to pay us, if you pay, Salesforce, Inc.” The site said the deadline for payment was Friday.

In an email Wednesday, a Salesforce representative said the company is spurning the demand.

Salesforce says it won’t pay extortion demand in 1 billion records breach Read More »

synology-caves,-walks-back-some-drive-restrictions-on-upcoming-nas-models

Synology caves, walks back some drive restrictions on upcoming NAS models


Policy change affects at least 2025 model Plus, Value, and J-series DiskStations.

Credit: SOPA Images / Getty

If you were considering the purchase of a Synology NAS but were leery of the unreasonably high cost of populating it with special Synology-branded hard disk drives, you can breathe a little easier today. In a press release dated October 8, Synology noted that with the release of its latest Disk Station Manager (DSM) update, some of its 2025 model-year products—specifically, the Plus, Value, and J-series DiskStation NAS devices—would “support the installation and storage pool creation of non-validated third-party drives.”

This unexpected move comes just a few months after Synology aggressively expanded its “verified drive” policy down-market to the entire Plus line of DiskStations. Prior to today, the network-attached storage vendor had shown no signs of swerving from the decision, painting it as a pro-consumer move intended to enhance reliability. “Extensive internal testing has shown that drives that follow a rigorous validation process when paired with Synology systems are at less risk of drive failure and ongoing compatibility issues,” Synology previously claimed in an email to Ars.

What is a “verified” or “validated” drive?

Synology first released its own brand of hard disk drives back in 2021 and began requiring their use in a small but soon-to-increase number of its higher-end NAS products. Although the drives were rebadged offerings from other manufacturers—there are very few hard disk drive OEMs, and Synology isn’t one of them—the company claimed that its branded disks underwent significant additional validation and testing that, when coupled with customized firmware, yielded reliability and performance improvements over off-the-shelf components.

However, those drives came with what was in some cases a substantial price increase over commodity hardware. Although I couldn’t find an actual published MSRP list, some spot checking on several web stores shows that the Synology HAT5310 enterprise SATA drive (a drive with the same warranty and expected service life as a Seagate Exos or Western Digital Gold) is available in 8TB at $299, 12TB at $493, and 20TB at an eye-watering $605. (For comparison, identically sized Seagate Exos disks are $220 at 8TB, $345 at 12TB, and $399 at 20TB.) Other Synology drive models tell similar pricing stories.

Photograph of a synology nas in profile

A Synology DS1525+ NAS, which up until today would scream at you unless you filled it with special Synology-branded disks.

Credit: Synology

A Synology DS1525+ NAS, which up until today would scream at you unless you filled it with special Synology-branded disks. Credit: Synology

If you put non-verified drives in a Synology NAS that required verified drives, certain functionality would be reduced or potentially removed, depending on the specific model disks you were introducing. Additionally, the Synology DSM interface would spam you with large “DANGER” warnings that your data might not be safe. Synology also at first refused to display S.M.A.R.T. diagnostic information from unverified drives, though this particular restriction was eventually lifted.

Savvy sysadmins could disable the verified drive requirements altogether by using one of several different workarounds, though that kind of thing opens one up to a different kind of danger—the danger of depending on an unsupported configuration tweak to keep a production system fully online and functional. It’s not a big deal for home users, but for business users relying on a Synology system at work with people’s livelihoods involved, the should-I-or-shouldn’t-I calculus of using such a workaround gets murkier. Synology is likely banking on the fact that if your business is of a certain size and you’re spending someone else’s money, a few hundred bucks more on each disk drive for peace of mind and a smoothly functioning NAS might seem like less of a speed bump than it would to a homelab admin spending money out of their own pocket.

While Synology’s claims about its validated drives having undergone extensive testing and yielding some performance benefit do hold water (at least under the specific benchmark circumstances called out on Synology drive page), it’s very difficult for me to see Synology’s actions here as anything other than an attempt to squeeze additional revenue out of what the company thought to be an exploitable market segment.

Enterprise storage companies like Dell-EMC enjoy vast margins on high-end storage gear—margins that don’t exist down in the consumer and SMB space where Synology is usually found. So the company decided to be the change it wanted to see in the world and created a way to extract those margins by making expensive custom hard disk drives mandatory (at least in a “nice data you got there, it’d be a shame if something happened to it—better use our disks” kind of way) for more and more products.

Unfortunately for Synology, today is not 2021, and the prosumer/SMB NAS market is getting downright crowded. In addition to long-time players like QNAP that continue to pump out new products, up-and-comer UGREEN is taking market share from Synology in the consumer areas where Synology has traditionally been most successful, and even Ubiquiti is making a run at the mid-market with its own line of Unifi-integrated NAS devices. Synology’s verified drive rent-seeking has made the brand practically impossible to recommend over competitors’ offerings for any use case without significant caveats. At least, up until today’s backpedaling.

When asked about the reasoning behind the change, a Synology representative gave the following statement via email: “First and foremost, our goal is to create reliable and secure solutions for user’s data, which is what drives our decisions as a company, including this original one. We are continuing with our validation program, working with third-party vendors to test their drives under the same rigorous testing we put our branded drives through, so we will still uphold those standards that we have set for ourselves. However, based on user feedback and to provide more flexibility in drive choices since testing third party drives has taken a while, we’re opening up the drive policy to include non-verified drives.”

As part of the same exchange, I asked Synology if they’re aware that—at least anecdotally, from what I see among the IT-savvy Ars audience—that this change has caused reputational damage among a significant number of existing and potential Synology customers. “While our original goal was to improve system reliability by focusing on a smaller set of validated configurations,” the company representative replied, “our valued community has shared feedback that flexibility is equally important. We are committed to our user’s experience and we understand that this decision didn’t align with their expectations of us. We value their input and will utilize it as we move forward.”

The about-face

As of the October 8 release of DSM 7.3, the input has been utilized. Here’s the full section from the company’s DSM 7.3 announcement:

As a part of its mission statement, Synology is committed to delivering reliable, high-performance storage systems. This commitment has led to a standardized process of rigorous testing and validation for both hardware and software components, and has been an integral part of Synology’s development approach for many years. Both Synology storage drives and components validated through the third-party program undergo uniform testing processes to ensure they are able to provide the highest levels of reliability with DSM.

Synology is currently collaborating closely with third-party drive manufacturers to accelerate the testing and verification of additional storage drives, and will announce more updates as soon as possible. In the meantime, 25 model year DiskStation Plus, Value, and J series running DSM 7.3 will support the installation and storage pool creation of non-validated third-party drives. This provides users greater flexibility while Synology continues to expand the lineup of officially verified drives that meet long-term reliability standards.

The upshot is that the validated drive requirements are being removed from 2025 model-year Plus, Value, and J-series NAS devices. (Well, mostly removed—the press release indicates that pool and cache creation on M.2 disks “still requires drives on the HCL [hardware compatibility list].”)

We asked Synology whether the requirements will also be lifted from previous-generation Synology products—and the answer to that question appears to be a “no.”

“This change only affects the ’25 series models: DS725+, DS225+, DS425+, DS925+, DS1525+, DS1825+. Models in the xs+ line, like the DS3622xs+, are considered a business/enterprise model and will remain under the current HCL policy for our business lines,” Synology explained.

Updated with comments from Synology.

Photo of Lee Hutchinson

Lee is the Senior Technology Editor, and oversees story development for the gadget, culture, IT, and video sections of Ars Technica. A long-time member of the Ars OpenForum with an extensive background in enterprise storage and security, he lives in Houston.

Synology caves, walks back some drive restrictions on upcoming NAS models Read More »

amd-wins-massive-ai-chip-deal-from-openai-with-stock-sweetener

AMD wins massive AI chip deal from OpenAI with stock sweetener

As part of the arrangement, AMD will allow OpenAI to purchase up to 160 million AMD shares at 1 cent each throughout the chips deal.

OpenAI diversifies its chip supply

With demand for AI compute growing rapidly, companies like OpenAI have been looking for secondary supply lines and sources of additional computing capacity, and the AMD partnership is part the company’s wider effort to secure sufficient computing power for its AI operations. In September, Nvidia announced an investment of up to $100 billion in OpenAI that included supplying at least 10 gigawatts of Nvidia systems. OpenAI plans to deploy a gigawatt of Nvidia’s next-generation Vera Rubin chips in late 2026.

OpenAI has worked with AMD for years, according to Reuters, providing input on the design of older generations of AI chips such as the MI300X. The new agreement calls for deploying the equivalent of 6 gigawatts of computing power using AMD chips over multiple years.

Beyond working with chip suppliers, OpenAI is widely reported to be developing its own silicon for AI applications and has partnered with Broadcom, as we reported in February. A person familiar with the matter told Reuters the AMD deal does not change OpenAI’s ongoing compute plans, including its chip development effort or its partnership with Microsoft.

AMD wins massive AI chip deal from OpenAI with stock sweetener Read More »

ice-wants-to-build-a-24/7-social-media-surveillance-team

ICE wants to build a 24/7 social media surveillance team

Together, these teams would operate as intelligence arms of ICE’s Enforcement and Removal Operations division. They will receive tips and incoming cases, research individuals online, and package the results into dossiers that could be used by field offices to plan arrests.

The scope of information contractors are expected to collect is broad. Draft instructions specify open-source intelligence: public posts, photos, and messages on platforms from Facebook to Reddit to TikTok. Analysts may also be tasked with checking more obscure or foreign-based sites, such as Russia’s VKontakte.

They would also be armed with powerful commercial databases such as LexisNexis Accurint and Thomson Reuters CLEAR, which knit together property records, phone bills, utilities, vehicle registrations, and other personal details into searchable files.

The plan calls for strict turnaround times. Urgent cases, such as suspected national security threats or people on ICE’s Top Ten Most Wanted list, must be researched within 30 minutes. High-priority cases get one hour; lower-priority leads must be completed within the workday. ICE expects at least three-quarters of all cases to meet those deadlines, with top contractors hitting closer to 95 percent.

The plan goes beyond staffing. ICE also wants algorithms, asking contractors to spell out how they might weave artificial intelligence into the hunt—a solicitation that mirrors other recent proposals. The agency has also set aside more than a million dollars a year to arm analysts with the latest surveillance tools.

ICE did not immediately respond to a request for comment.

Earlier this year, The Intercept revealed that ICE had floated plans for a system that could automatically scan social media for “negative sentiment” toward the agency and flag users thought to show a “proclivity for violence.” Procurement records previously reviewed by 404 Media identified software used by the agency to build dossiers on flagged individuals, compiling personal details, family links, and even using facial recognition to connect images across the web. Observers warned it was unclear how such technology could distinguish genuine threats from political speech.

ICE wants to build a 24/7 social media surveillance team Read More »

why-irobot’s-founder-won’t-go-within-10-feet-of-today’s-walking-robots

Why iRobot’s founder won’t go within 10 feet of today’s walking robots

In his post, Brooks recounts being “way too close” to an Agility Robotics Digit humanoid when it fell several years ago. He has not dared approach a walking one since. Even in promotional videos from humanoid companies, Brooks notes, humans are never shown close to moving humanoid robots unless separated by furniture, and even then, the robots only shuffle minimally.

This safety problem extends beyond accidental falls. For humanoids to fulfill their promised role in health care and factory settings, they need certification to operate in zones shared with humans. Current walking mechanisms make such certification virtually impossible under existing safety standards in most parts of the world.

Apollo robot

The humanoid Apollo robot. Credit: Google

Brooks predicts that within 15 years, there will indeed be many robots called “humanoids” performing various tasks. But ironically, they will look nothing like today’s bipedal machines. They will have wheels instead of feet, varying numbers of arms, and specialized sensors that bear no resemblance to human eyes. Some will have cameras in their hands or looking down from their midsections. The definition of “humanoid” will shift, just as “flying cars” now means electric helicopters rather than road-capable aircraft, and “self-driving cars” means vehicles with remote human monitors rather than truly autonomous systems.

The billions currently being invested in forcing today’s rigid, vision-only humanoids to learn dexterity will largely disappear, Brooks argues. Academic researchers are making more progress with systems that incorporate touch feedback, like MIT’s approach using a glove that transmits sensations between human operators and robot hands. But even these advances remain far from the comprehensive touch sensing that enables human dexterity.

Today, few people spend their days near humanoid robots, but Brooks’ 3-meter rule stands as a practical warning of challenges ahead from someone who has spent decades building these machines. The gap between promotional videos and deployable reality remains large, measured not just in years but in fundamental unsolved problems of physics, sensing, and safety.

Why iRobot’s founder won’t go within 10 feet of today’s walking robots Read More »

ars-live:-is-the-ai-bubble-about-to-pop?-a-live-chat-with-ed-zitron.

Ars Live: Is the AI bubble about to pop? A live chat with Ed Zitron.

As generative AI has taken off since ChatGPT’s debut, inspiring hundreds of billions of dollars in investments and infrastructure developments, the top question on many people’s minds has been: Is generative AI a bubble, and if so, when will it pop?

To help us potentially answer that question, I’ll be hosting a live conversation with prominent AI critic Ed Zitron on October 7 at 3: 30 pm ET as part of the Ars Live series. As Ars Technica’s senior AI reporter, I’ve been tracking both the explosive growth of this industry and the mounting skepticism about its sustainability.

You can watch the discussion live on YouTube when the time comes.

Zitron is the host of the Better Offline podcast and CEO of EZPR, a media relations company. He writes the newsletter Where’s Your Ed At, where he frequently dissects OpenAI’s finances and questions the actual utility of current AI products. His recent posts have examined whether companies are losing money on AI investments, the economics of GPU rentals, OpenAI’s trillion-dollar funding needs, and what he calls “The Subprime AI Crisis.”

Alt text for this image:

Credit: Ars Technica

During our conversation, we’ll dig into whether the current AI investment frenzy matches the actual business value being created, what happens when companies realize their AI spending isn’t generating returns, and whether we’re seeing signs of a peak in the current AI hype cycle. We’ll also discuss what it’s like to be a prominent and sometimes controversial AI critic amid the drumbeat of AI mania in the tech industry.

While Ed and I don’t see eye to eye on everything, his sharp criticism of the AI industry’s excesses should make for an engaging discussion about one of tech’s most consequential questions right now.

Please join us for what should be a lively conversation about the sustainability of the current AI boom.

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that-annoying-sms-phish-you-just-got-may-have-come-from-a-box-like-this

That annoying SMS phish you just got may have come from a box like this

Scammers have been abusing unsecured cellular routers used in industrial settings to blast SMS-based phishing messages in campaigns that have been ongoing since 2023, researchers said.

The routers, manufactured by China-based Milesight IoT Co., Ltd., are rugged Internet of Things devices that use cellular networks to connect traffic lights, electric power meters, and other sorts of remote industrial devices to central hubs. They come equipped with SIM cards that work with 3G/4G/5G cellular networks and can be controlled by text message, Python scripts, and web interfaces.

An unsophisticated, yet effective, delivery vector

Security company Sekoia on Tuesday said that an analysis of “suspicious network traces” detected in its honeypots led to the discovery of a cellular router being abused to send SMS messages with phishing URLs. As company researchers investigated further, they identified more than 18,000 such routers accessible on the Internet, with at least 572 of them allowing free access to programming interfaces to anyone who took the time to look for them. The vast majority of the routers were running firmware versions that were more than three years out of date and had known vulnerabilities.

The researchers sent requests to the unauthenticated APIs that returned the contents of the routers’ SMS inboxes and outboxes. The contents revealed a series of campaigns dating back to October 2023 for “smishing”—a common term for SMS-based phishing. The fraudulent text messages were directed at phone numbers located in an array of countries, primarily Sweden, Belgium, and Italy. The messages instructed recipients to log in to various accounts, often related to government services, to verify the person’s identity. Links in the messages sent recipients to fraudulent websites that collected their credentials.

“In the case under analysis, the smishing campaigns appear to have been conducted through the exploitation of vulnerable cellular routers—a relatively unsophisticated, yet effective, delivery vector,” Sekoia researchers Jeremy Scion and Marc N. wrote. “These devices are particularly appealing to threat actors, as they enable decentralized SMS distribution across multiple countries, complicating both detection and takedown efforts.”

That annoying SMS phish you just got may have come from a box like this Read More »

openai’s-sora-2-lets-users-insert-themselves-into-ai-videos-with-sound

OpenAI’s Sora 2 lets users insert themselves into AI videos with sound

On Tuesday, OpenAI announced Sora 2, its second-generation video-synthesis AI model that can now generate videos in various styles with synchronized dialogue and sound effects, which is a first for the company. OpenAI also launched a new iOS social app that allows users to insert themselves into AI-generated videos through what OpenAI calls “cameos.”

OpenAI showcased the new model in an AI-generated video that features a photorealistic version of OpenAI CEO Sam Altman talking to the camera in a slightly unnatural-sounding voice amid fantastical backdrops, like a competitive ride-on duck race and a glowing mushroom garden.

Regarding that voice, the new model can create what OpenAI calls “sophisticated background soundscapes, speech, and sound effects with a high degree of realism.” In May, Google’s Veo 3 became the first video-synthesis model from a major AI lab to generate synchronized audio as well as video. Just a few days ago, Alibaba released Wan 2.5, an open-weights video model that can generate audio as well. Now OpenAI has joined the audio party with Sora 2.

OpenAI demonstrates Sora 2’s capabilities in a launch video.

The model also features notable visual consistency improvements over OpenAI’s previous video model, and it can also follow more complex instructions across multiple shots while maintaining coherency between them. The new model represents what OpenAI describes as its “GPT-3.5 moment for video,” comparing it to the ChatGPT breakthrough during the evolution of its text-generation models over time.

Sora 2 appears to demonstrate improved physical accuracy over the original Sora model from February 2024, with OpenAI claiming the model can now simulate complex physical movements like Olympic gymnastics routines and triple axels while maintaining realistic physics. Last year, shortly after the launch of Sora 1 Turbo, we saw several notable failures of similar video-generation tasks that OpenAI claims to have addressed with the new model.

“Prior video models are overoptimistic—they will morph objects and deform reality to successfully execute upon a text prompt,” OpenAI wrote in its announcement. “For example, if a basketball player misses a shot, the ball may spontaneously teleport to the hoop. In Sora 2, if a basketball player misses a shot, it will rebound off the backboard.”

OpenAI’s Sora 2 lets users insert themselves into AI videos with sound Read More »

california’s-newly-signed-ai-law-just-gave-big-tech-exactly-what-it-wanted

California’s newly signed AI law just gave Big Tech exactly what it wanted

On Monday, California Governor Gavin Newsom signed the Transparency in Frontier Artificial Intelligence Act into law, requiring AI companies to disclose their safety practices while stopping short of mandating actual safety testing. The law requires companies with annual revenues of at least $500 million to publish safety protocols on their websites and report incidents to state authorities, but it lacks the stronger enforcement teeth of the bill Newsom vetoed last year after tech companies lobbied heavily against it.

The legislation, S.B. 53, replaces Senator Scott Wiener’s previous attempt at AI regulation, known as S.B. 1047, that would have required safety testing and “kill switches” for AI systems. Instead, the new law asks companies to describe how they incorporate “national standards, international standards, and industry-consensus best practices” into their AI development, without specifying what those standards are or requiring independent verification.

“California has proven that we can establish regulations to protect our communities while also ensuring that the growing AI industry continues to thrive,” Newsom said in a statement, though the law’s actual protective measures remain largely voluntary beyond basic reporting requirements.

According to the California state government, the state houses 32 of the world’s top 50 AI companies, and more than half of global venture capital funding for AI and machine learning startups went to Bay Area companies last year. So while the recently signed bill is state-level legislation, what happens in California AI regulation will have a much wider impact, both by legislative precedent and by affecting companies that craft AI systems used around the world.

Transparency instead of testing

Where the vetoed SB 1047 would have mandated safety testing and kill switches for AI systems, the new law focuses on disclosure. Companies must report what the state calls “potential critical safety incidents” to California’s Office of Emergency Services and provide whistleblower protections for employees who raise safety concerns. The law defines catastrophic risk narrowly as incidents potentially causing 50+ deaths or $1 billion in damage through weapons assistance, autonomous criminal acts, or loss of control. The attorney general can levy civil penalties of up to $1 million per violation for noncompliance with these reporting requirements.

California’s newly signed AI law just gave Big Tech exactly what it wanted Read More »

can-ai-detect-hedgehogs-from-space?-maybe-if-you-find-brambles-first.

Can AI detect hedgehogs from space? Maybe if you find brambles first.

“It took us about 20 seconds to find the first one in an area indicated by the model,” wrote Jaffer in a blog post documenting the field test. Starting at Milton Community Centre, where the model showed high confidence of brambles near the car park, the team systematically visited locations with varying prediction levels.

The research team locating their first bramble.

The research team locating their first bramble. Credit: Sadiq Jaffer

At Milton Country Park, every high-confidence area they checked contained substantial bramble growth. When they investigated a residential hotspot, they found an empty plot overrun with brambles. Most amusingly, a major prediction in North Cambridge led them to Bramblefields Local Nature Reserve. True to its name, the area contained extensive bramble coverage.

The model reportedly performed best when detecting large, uncovered bramble patches visible from above. Smaller brambles under tree cover showed lower confidence scores—a logical limitation given the satellite’s overhead perspective. “Since TESSERA is learned representation from remote sensing data, it would make sense that bramble partially obscured from above might be harder to spot,” Jaffer explained.

An early experiment

While the researchers expressed enthusiasm over the early results, the bramble detection work represents a proof-of-concept that is still under active research. The model has not yet been published in a peer-reviewed journal, and the field validation described here was an informal test rather than a scientific study. The Cambridge team acknowledges these limitations and plans more systematic validation.

However, it’s still a relatively positive research application of neural network techniques that reminds us that the field of artificial intelligence is much larger than just generative AI models, such as ChatGPT, or video synthesis models.

Should the team’s research pan out, the simplicity of the bramble detector offers some practical advantages. Unlike more resource-intensive deep learning models, the system could potentially run on mobile devices, enabling real-time field validation. The team considered developing a phone-based active learning system that would enable field researchers to improve the model while verifying its predictions.

In the future, similar AI-based approaches combining satellite remote sensing with citizen science data could potentially map invasive species, track agricultural pests, or monitor changes in various ecosystems. For threatened species like hedgehogs, rapidly mapping critical habitat features becomes increasingly valuable during a time when climate change and urbanization are actively reshaping the places that hedgehogs like to call home.

Can AI detect hedgehogs from space? Maybe if you find brambles first. Read More »

experts-urge-caution-about-using-chatgpt-to-pick-stocks

Experts urge caution about using ChatGPT to pick stocks

“AI models can be brilliant,” Dan Moczulski, UK managing director at eToro, told Reuters. “The risk comes when people treat generic models like ChatGPT or Gemini as crystal balls.” He noted that general AI models “can misquote figures and dates, lean too hard on a pre-established narrative, and overly rely on past price action to attempt to predict the future.”

The hazards of AI stock picking

Using AI to trade stocks at home feels like it might be the next step in a long series of technological advances that have democratized individual retail investing, for better or for worse. Computer-based stock trading for individuals dates back to 1984, when Charles Schwab introduced electronic trading services for dial-up customers. E-Trade launched in 1992, and by the late 1990s, online brokerages had transformed retail investing, dropping commission fees from hundreds of dollars per trade to under $10.

The first “robo-advisors” appeared after the 2008 financial crisis, which began the rise of automated online services that use algorithms to manage and rebalance portfolios based on a client’s goals. Services like Betterment launched in 2010, and Wealthfront followed in 2011, using algorithms to automatically rebalance portfolios. By the end of 2015, robo-advisors from nearly 100 companies globally were managing $60 billion in client assets.

The arrival of ChatGPT in November 2022 arguably marked a new phase where retail investors could directly query an AI model for stock picks rather than relying on pre-programmed algorithms. But Leung acknowledged that ChatGPT cannot access data behind paywalls, potentially missing crucial analyses available through professional services. To get better results, he creates specific prompts like “assume you’re a short analyst, what is the short thesis for this stock?” or “use only credible sources, such as SEC filings.”

Beyond chatbots, reliance on financial algorithms is growing. The “robo-advisory” market, which includes all companies providing automated, algorithm-driven financial advice from fintech startups to established banks, is forecast to grow roughly 600 percent by 2029, according to data-analysis firm Research and Markets.

But as more retail investors turn to AI tools for investment decisions, it’s also potential trouble waiting to happen.

“If people get comfortable investing using AI and they’re making money, they may not be able to manage in a crisis or downturn,” Leung warned Reuters. The concern extends beyond individual losses to whether retail investors using AI tools understand risk management or have strategies for when markets turn bearish.

Experts urge caution about using ChatGPT to pick stocks Read More »