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Generative AI (genAI) could help people live longer and healthier lives, transform education, solve climate change, help protect endangered animals, speed up disaster response, and make work more creative, all while making daily life safer and more humane for billions worldwide. 

Or the technology could lead to massive job losses, boost cybercrime, empower rogue states, arm terrorists, enable scams, spread deepfakes and election manipulation, end democracy, and possibly lead to human extinction. 

Well, humanity? What’s it going to be?

California’s dreamin’

Last year, the California State Legislature passed a bill that would have required companies based in the state to perform expensive safety tests for large genAI models and also build in “kill switches” that could stop the technology from going rogue. 

If this kind of thing doesn’t sound like a job for state government, consider that California’s genAI companies include OpenAI, Google, Meta, Apple, Nvidia, Salesforce, Oracle, Anthropic, Anduril, Tesla, and Intel. 

The biggest genAI company outside California is Amazon; it’s based in Washington state, but has its AI division in California.

Anyway, California Gov. Gavin Newsom vetoed the bill. Instead, he asked AI experts, including Fei-Fei Li of Stanford, to recommend a policy less onerous to the industry. The resulting Joint California Policy Working Group on AI Frontier Models released a 52-page report this past week. 

The report focused on transparency, rather than testing mandates, as the solution to preventing genAI harms. The recommendation also included third-party risk assessments, whistleblower protections, and flexible rules based on real-world risk, much of which was also in the original bill. 

It’s unclear whether the legislature will incorporate the recommendations into a new bill. In general, the legislators have reacted favorably to the report, but AI companies have expressed concern about the transparency part, fearing they’ll have to reveal their secrets to competitors. 

Two kinds of risk

There are three fundamental ways that emerging AI systems could create problems and even catastrophes to people: 

1. Misalignment. Some experts fear that misaligned AI, acting creatively and automatically, will operate in its own self-interest and against the interests of people. Research and media reports show that advanced AI systems can lie, cheat, and engage in deceptive behavior. GenAI models have been caught faking compliance, hiding their true intentions, and even strategically misleading their human overseers when it serves their goals; that was seen in experiments with models like Anthropic’s Claude and Meta’s CICERO, which lied and betrayed allies in the game Diplomacy despite being trained for honesty.

2. Misuse. Malicious people, organizations, and governments could use genAI tools to launch highly effective cyberattacks, create convincing deepfakes, manipulate public opinion, automate large-scale surveillance, and control autonomous weapons or vehicles for destructive purposes. These capabilities could enable mass disruption, undermine trust, destabilize societies, and threaten lives on an unprecedented scale.

3. The collective acting on bad incentives. AI risk isn’t a simple story of rogue algorithms or evil hackers. Harms could result from collective self-interest combined with incompetence or regulatory failure. For example, when genAI-driven machines replace human workers, it’s not just the tech companies chasing efficiency. It’s also the policymakers who didn’t adopt labor laws, the business leaders who made the call, and consumers demanding ever-cheaper products. 

What’s interesting about this list of ways AI could cause harm is that all are nearly certain to happen. We know that because it’s already happening at scale, and the only certain change coming in the future is the rapidly growing power of AI. 

So, how shall we proceed? 

We can all agree that genAI is a powerful tool that is becoming more capable all the time. We want to maximize its benefit to people and minimize its threat. 

So, here’s what I believe is the question of the decade: What do we do to promote this outcome? By “we,” I mean the technology professionals, buyers, leaders, and thought leaders reading this column. 

What should we be doing, advocating, supporting, or opposing? 

I asked Andrew Rogoyski, director of Innovation and Partnerships at the UK’s Surrey Institute for People-Centred Artificial Intelligence, that question. Rogoyski works full-time to maximize AI’s benefits and minimize its harms. 

One concern with genAI systems, according to Rogoyski, is that we’re entering a realm where nobody knows how they work — even when they benefit people. As AI gets more capable, “new products appear, new materials, new medicines, we cure cancer. But actually, we won’t have any idea how it’s done,” he said. 

“One of the challenges is these decisions are being made by a few companies and a few individuals within those companies,” he said. Decisions made by a few people “will have enormous impact on…global society as a whole. And that doesn’t feel right.” He pointed out that companies like Amazon, OpenAI, and Google have far more money to devote to AI than entire governments. 

Rogoyski pointed out the conundrum exposed by solutions like the one California is trying to arrive at. At the core of the California Policy Working Group’s proposal is transparency, treating AI functionality as a kind of open-source project. On the one hand, outside experts can help flag dangers. On the other, transparency opens the technology to malicious actors. He gave the example of AI designed for biotech, something designed to engineer life-saving drugs. In the wrong hands, that same tool might be used to engineer a catastrophic bio-weapon.

According to Rogoyski, the solution won’t be found solely in some grand legislation or the spontaneous emergence of ethics in the hearts of Silicon Valley billionaires. The solution will involve broad-scale collective action by just about everyone.

It’s up to us

At the grass-roots level, we need to advocate the practice of basing our purchasing, use, and investment in AI systems that are serious about and capable with ethical practices, strong safety policies, and deep concern about alignment. 

We all need to favor companies that “do the right thing in the sense of sharing information about how they trained [their AI], what measures they put in place to stop it misbehaving and so on,” said Rogoyski.

Beyond that, we need stronger regulation based more on expert input and less on Silicon Valley businesses’ trillion-dollar aspirations. We need broad cooperation between companies and universities. 

We also need to support, in any way we can, the application of AI to our most pressing problems, including medicine, energy, climate change, income inequality, and others.

Rogoyski offers general advice for anyone worried about losing their job to AI: Look to the young. 

While older professionals might look at AI and feel threatened by it, younger people often see opportunity. “If you talk to some young creative who’s just gone to college [and] come out with a [degree in] photography, graphics, whatever it is,” he said, “They’re tremendously excited about these tools because they’re now able to do things that might have taken a $10 million budget.”

In other words, look for opportunities in AI to accelerate, enhance, and empower your own work.

And that’s generally the mindset we should all embrace: We are not powerless. We are powerful. AI is here to stay, and it’s up to all of us to make it work better for ourselves, our communities, our nations, and our world. 

Source:: Computer World

Contactless payments such as Apple Pay and sustainability in inventory control are going to get much easier with an upcoming update to the Near Field Communications (NFC) standard that will make devices connect more swiftly and support the Digital Product Passport (NDPP) specification.

The first problems the new standard solves are range and reliability. At present, standard NFC supports a range of up to 0.2 inches and the connections aren’t always robust. What that means to most of us is the need to wriggle your iPhone or Apple Watch around a little to gain connection to the payment terminal. The improved NFC increases that range to to about 3/4 of an inch for all devices and makes the connection a little more resilient; the standard is also a little faster, which means once you authorize a payment it will take place faster than it already does.

Faster connections, easier payments, and more

That range and reliability improvements aren’t just for mobile payments, of course. If you use your iPhone as a car key or have mobile transit cards in your Apple Wallet, you should get a much better experience when opening doors or catching public transit. The NFC update also comes as Apple prepares to introduce expanded support for digital IDs and in-store payments with iOS 16. The latter is interesting because while the NFC Forum didn’t say anything about it, the update does support more complex transactions over NFC — that should make it easier to use supermarket loyalty cards at the same time as Apple Pay in a single tap. The Forum calls these, “multi-purpose tap use cases where a single tap unlocks multiple functions.”

NFC Release 15 is also expected to advance new and exciting use cases, such as using your mobile phone as a payment terminal, championing sustainability and optimizing NFC use across a variety of sectors, including automotive, transit and access control. There is also support for a new feature that has been designed to meet emerging sustainability regulations: NFC Digital Product Passport (NDPP)

What is NDPP and is it safe?

Aimed at manufacturers, NDPP is a framework to allow a single NFC tag embedded in a product to store and transmit both standard and extended Digital Product Passport (DPP) data using NFC. That data includes information such as a product’s composition, origin, environmental, lifestyle, and recycling details. Most hardware manufacturers will need to begin capturing this kind of information under an incoming EU law known as the Ecodesign for Sustainable Products Regulation (ESPR). The information is meant to be made available to customers, business users and recyclers and designed to boost transparency and sustainability. It will be interesting, for example, to use DPP inside future iPhones to determine where the device and its components originate – and it might be fun to explore refurbished devices to see whether components installed to return them to use have been used in different devices previously. 

That said, this kind of unique device information does sound like the kind of data that could be abused for device fingerprinting and user tracking; is there a risk of this?

Age of consent

I contacted Mike McCamon, the organization’s executive director, for more background on NDPP. I was particularly curious about the NDPP specification — could it be abused for digital device fingerprinting? That’s unlikely, said McCarmon, in part because of the nature of NFC design, which has been developed from day one to require active consent from the user.

“Security and privacy are foundational aspects of our work at the NFC Forum,” he said. “The NFC Digital Product Passport (NDPP) Specification can be thought more of a container of content than being fully descriptive of what content is included.” The support should extend use of NFC in different ways, such as in supply chain management, inventory control, or effective recycling strategies, all of which may benefit from the kind of information NDPP provides.

“And of course, even with our new extended range…, NFC Forum-capable products must be in the closest of proximity to be read. This is in addition to most NFC functionality today on mobile devices and wearables, which is only accessible following a direct user action – like a double-tap for instance. For these and the reasons above, we believe NFC Forum standards will provide the most capable, intuitive, and secure data carrier of DPP data for the market.”

For the rest of us

Millions of people use NFC every day for payments, car and hotel rooms, or even travel. That means the new NFC standard will deliver measurable benefits to consumers because it should work better than it does now. And for enterprises, the extended support for Multi-Purpose Taps should make for a variety of product and service development possibilities, particularly as Apple opens up access to NFC on its devices.

The NFC Release 15 is currently available to high-level NFC Forum member companies, including Apple, Google, Sony, and Huawei, who can now implement the improvements in their own products in advance of a public release as new iPhones appear in fall.

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Source:: Computer World

By Thomas Macaulay The race to dominate AI infrastructure has left Europe trailing the US — but the continent still has a shot at global leadership in AI apps. That was the verdict of Dutch tech leaders at the Assembly, the invite-only policy track of TNW Conference in Amsterdam. While Silicon Valley controls the scaffolding for AI, they urged Europe to focus on building apps on top. Leading the call was Jeroen van Glabbeek, CEO and founder of CM.com, a customer engagement platform with a market cap of around €217mn and annual revenues of €274mn in 2024. Van Glabbeek believes the US advantage in…This story continues at The Next Web

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In a move that could redefine the boundaries between generative AI (genAI) and intellectual property, Disney and Universal have joined forces to file a lawsuit against Midjourney, one of the world’s most popular AI image generators. 

You may think you’ve heard this story before — The New York Times‘ 2023 lawsuit against OpenAI and Microsoft and News Corp. vs. Perplexity — but this case is different. For one thing, this is the first time major Hollywood studios with far more cash to prosecute the case have directly targeted a genAI company for copyright infringement. For another, Disney and Universal are both big AI users.

Disney and Universal allege that Midjourney’s platform is a “bottomless pit of plagiarism.” With Midjourney, all a subscriber need do to create unauthorized images of iconic characters such as Darth Vader, Elsa, the Minions, Shrek, and many others is to type in a prompt.

Original ‘Iron Man’ image is on the left; genAI-created image is on the right. 
Disney/Universal lawsuit

Original image is on the left; genAI image is on the right. 
Disney/Univeral lawsuit

There’s no question anyone can do it. If you don’t feel like trying it yourself, just look at some of the images in the Disney/Universal lawsuit complaint (shown above).

Can you tell which ones are the original from Avengers: Infinity War and which were generated by Midjourney? I can’t, and I have a good eye for this kind of thing. GenAI image creation has come a long way since all you had to do was count the number of fingers. (The originals are on the left.)

This didn’t require some kind of fancy prompt. As researchers have found, all you had to do to generate them was name the character and use the keyword “screencap,” and you quickly received your fake image. Or you could simply ask for “master super villain” or “armored superhero.” 

“This is not a ‘close call’ under well-settled copyright law,” the lawsuit claims. 

Correct. It’s not close at all.

In the company’s defense — if you can call it that — Midjourney CEO David Holz is on record as saying his AI has been trained on  “just a big scrape of the Internet.” What about copyrights on these images? 

“There isn’t really a way to get a hundred million images and know where they’re coming from. It would be cool if images had metadata embedded in them about the copyright owner or something. But that’s not a thing; there’s not a registry. There’s no way to find a picture on the Internet, and then automatically trace it to an owner and then have any way of doing anything to authenticate it.”

I think when it comes to Disney, it’s pretty darn obvious who owns the images. I mean, this is Disney, the big bad wolf of copyright. After Walt Disney lost the copyright to his earlier character, Oswald the Lucky Rabbit, he made darn sure that, starting with Mickey Mouse in 1928, he’d lock down its intellectual property for as close to forever as he could.

Indeed, over the decades, Disney has been behind laws to increase copyright coverage from a maximum of 56 years in 1928 to 75 years with the Copyright Act of 1976, and then 95 years with the Sonny Bono Copyright Term Extension Act (CTEA) of 1998, better known as the “Mickey Mouse Protection Act.” 

Disney has also never been shy about suing anyone who’d dare come close to their copyrighted images.  For example, in 1989, Disney threatened legal action against three daycare centers in Hallandale, FL., for painting murals of Disney characters such as Mickey Mouse, Donald Duck, and Goofy on their walls. 

Why? Because it’s all about the Benjamins. 

Disney, and to a lesser extent Universal, live and die from monetizing their intellectual property (IP). Mind you, much of that IP is generated from the public domain. As the Center for the Study of the Public Domain noted: “The public domain is Disney’s bread and butter. Frozen was inspired by Hans Christian Andersen’s The Snow Queen. … Alice in Wonderland, Snow White, The Hunchback of Notre Dame, Sleeping Beauty, Cinderella, The Little Mermaid, and Pinocchio came from stories by Lewis Carroll, The Brothers Grimm, Victor Hugo, Charles Perrault, Hans Christian Anderson, and Carlo Collodi.”

What Disney did with the public domain, MidJourney, and the rest of the AI companies want to do with pretty much everything on the Internet. OpenAI CEO Sam Altman, for instance,  has consistently argued that training genAI on copyrighted data should be considered “fair use.” He’s not alone.

On the other side of the fence, Disney and Universal’s lawsuit is not just about damages, which the pair puts at $150,000 per infringed work, but about setting a precedent. They want to stop Midjourney’s image and soon-to-be-launched video generation services in their tracks.

At the same time, the film studios freely admit they’re already using genAI themselves. Disney CEO Bob Iger has said the technology is already making Disney’s operations more efficient and enhancing creativity. “AI might indeed be the most potent technology our company has ever encountered, particularly in its capacity to enhance and allow consumers to access, experience, and appreciate our entertainment.” He also, of course, stressed that, “Given the speed that it is developing, we’re taking precautions to make sure of three things: One, that our IP is being protected. That’s incredibly important.”

This lawsuit is more than a Hollywood squabble; it’s a watershed moment in the ongoing debate over genAI, copyright, and the future of creative work. Previous cases have challenged the boundaries of fair use and data scraping, but none have involved the entertainment industry’s biggest players.

It might seem like a slam dunk for the Hollywood powerhouses. The images speak for themselves. But, if there’s one thing I’ve learned in covering IP cases, it’s that you never know what a court will decide.

Besides, there’s a real wild card. Donald Trump’s AI Action Plan is still a work in progress. The AI companies are arguing that it should give them permission to use pretty much anything as grist for their large language models (LLMs), while the media companies want all the copyright protection they can get. 

Which way will Trump’s officials jump? We don’t know. But I have a bad feeling about where they’ll go.

You see, what we do know is that after the Copyright Office released a pre-publication version of its 108-page copyright and AI report, which strived to strike a middle ground  “by supporting both of these world-class industries that contribute so much to our economic and cultural advancement.” However, it added that while some generative AI probably constitutes a “transformative” use, the mass scraping of all data did not qualify as fair use.

The result? The Trump administration, while not commenting on the report, fired Shira Perlmutter, the head of the Copyright Office, the next day. She’s been replaced by an attorney with no IP experience. 

Oh, also, hidden away in Trump’s “One Big Beautiful Bill” is a statement that imposes a 10-year ban on the enforcement of any state or local laws or regulations that “limit, restrict, or otherwise regulate” AI  models, AI systems, or automated decision systems. If that becomes law, whatever is in Trump’s AI Action Plan is what we’ll have to live with for the next few years.

As an author, I can’t tell you how unhappy that prospect makes me. I expect Trump to side with the AI companies, which means I can look forward to competing with my own repurposed work from here on out. 

Further reading:

AI vs. copyright

Court tosses hallucinated citation from Anthropic’s defense in copyright infringement case

Eleuther AI releases 8TB collection of licensed and open training data

>

Source:: Computer World

By Thomas Macaulay Europe must take bigger bets on young founders to build tomorrow’s tech giants, industry leaders urged today. Speaking at TNW Conference, investors and CEOs called for stronger support for entrepreneurial ambition — before Europe’s best ideas and brightest minds head elsewhere. Kieran Hill, General Partner at 20VC — a venture capital firm founded by podcast host Harry Stebbings — urged the continent’s institutions to expand their appetite for risk. “We need to change how we sell ambition,” he said. Hill believes changing this mindset is key to producing Europe’s next business leaders. He warned that today’s talented founders often want…This story continues at The Next Web

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By Siôn Geschwindt A saliva-based fertility tracker has received regulatory approval for use as a contraceptive in Europe. Developed by Berlin-based startup Inne, the at-home testing device — called the “Minilab” — tracks daily changes in progesterone levels, a hormone that plays a key role in regulating the menstrual cycle. It’s billed as a non-invasive alternative to hormonal birth control methods like the pill — and early tests have shown promising results. A year-long clinical study involving 300 women over 1,500 cycles found Inne’s at-home fertility tracker to be 100% effective when used perfectly, and 92% effective for typical use. That’s similar to the…This story continues at The Next Web

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OpenAI has ended its long-standing partnership with Scale AI, the company that powered some of the most complex data-labeling tasks behind frontier models such as GPT-4.

The split, confirmed by an OpenAI spokesperson to Bloomberg, comes on the heels of Meta’s $14.3 billion investment for a 49% stake in Scale, a move that industry analysts warn could redraw battle lines in the AI arms race.

It also secured Scale founder Alexandr Wang to lead Meta’s AI division, accelerating what Deepika Giri, AVP for BDA & AI Research, IDC Asia/Pacific described as a profound challenge to data neutrality in foundational AI layers. “The world is shifting toward vendor-neutral ecosystems,” Giri cautioned, where data security and open platforms are paramount. But with hyperscalers now commanding the core pipelines, that neutrality faces unprecedented pressure.

The high stakes of AI data and talent wars

Meta’s $29 billion valuation of Scale highlights its two-front war for both data infrastructure and elite talent. While the investment aims to shore up Llama 4’s competitiveness, the social giant is also offering unprecedented “seven-to-nine-figure” packages to lure top employees, including OpenAI staff reportedly targeted with $100 million offers, as CEO Sam Altman disclosed on the Uncapped podcast. Yet not all are swayed. A Menlo Ventures VC posted on X that many still choose OpenAI or Anthropic.

The fallout from OpenAI’s exit and Meta’s investment is poised to disrupt the data-labeling industry, projected to reach $29.2 billion by 2032. Jason Droege, Interim CEO, Scale, in a blog post, maintained that its data governance remains independent, stating, “nothing has changed about our commitment to protecting customer data.”

Those reassurances may already be falling short. OpenAI, Bloomberg reported, had already been quietly scaling back its use of Scale’s services for months, citing a need for more specialized data.

OpenAI’s exit redraws the AI data landscape

Scale, which began as a data-labeling pioneer built on a global contractor base in countries like India and Venezuela, reported $870 million in revenue for 2024. But with major clients like Google, which spent $150 million last year, its future is uncertain.

The CEO of Handshake, a Scale competitor, told Time that demand for his company’s services “tripled overnight” in the wake of the Meta deal. The exodus reflects a fear among Meta’s rivals that proprietary data and research roadmaps could leak to a competitor through Scale’s services.

This realignment also exposed blind spots in enterprise AI contracts. Most lack robust “change-of-control” clauses or vendor conflict safeguards, leaving companies exposed when partners align with rivals. As Ipsita Chakrabarty, an analyst at QKS Group, noted, many contracts still rely on static accuracy metrics that crumble against real-world data drift. The result, she warned, is that companies may end up “outsourcing intelligence but retaining liability for failures.”

Yet Scale’s value remains in its elite trainer network (historians, scientists, PhDs) handling specialized tasks costing reportedly “tens to hundreds of dollars” per unit. While Meta’s non-voting stake avoided automatic antitrust review, regulators may still investigate the blurred line between influence and control. For now, the full implications will take months to unfold, as regulatory reviews, vendor transitions, and internal audits continue to reshape the AI data supply chain.

The new realities of AI development

As companies such as Google rush to build in-house data labeling capabilities, the industry faces a choice to repeat the mistakes of the cloud consolidation era of 2010-2015 or take a more open route.

“We’re seeing history repeat itself,” observed Anushree Verma, senior director analyst at Gartner. “The AI race is causing vendor fragmentation now, but consolidation is inevitable.” The parallels are striking. Like cloud providers before them, AI giants are pushing vertical integration that risks locking enterprises into monolithic systems. She urged CIOs to prioritize “agile, interoperable solutions” as safeguards against monolithic systems.

This resonates with IDC’s suggestion for “vendor-neutral ecosystems where data security, regulatory compliance, and open platforms take center stage,” a philosophy now clashing with the industry’s walled-garden reality.

For CIOs, this moment demands more than procurement checklists. Successful AI adoption requires baking in “change management, decision traceability, and human-AI interaction design” from day one, QKS’ Chakrabarty.

The challenge now goes beyond compliance. It requires stress-testing AI ecosystems with the same urgency as applied to cloud and chip vulnerabilities. “The best approach,” according to IDC’s Giri, “is to evaluate capabilities independently and avoid deep integration across the stack, because a monolithic system may lack the flexibility to keep up with tomorrow’s needs.”

Source:: Computer World

Microsoft is set to cut thousands of jobs, mainly in sales, amid growing fears that AI advances are accelerating the replacement of human roles across the industry, Bloomberg reports.

The cuts follow a previous round in May, which saw approximately 6,000 roles eliminated.

Microsoft has been ramping up its AI investments to strengthen its position as enterprises across industries rush to integrate the technology into their operations.

Earlier this year, the company announced plans to spend around $80 billion in fiscal 2025, largely on building data centers to support AI training and cloud-based applications.

Adding to industry unease, Amazon CEO Andy Jassy said this week that generative AI and AI agents are expected to shrink the company’s corporate workforce over time.

AI or other factors?

AI is being used as an excuse for layoffs this year, but there may be more to it than what meets the eye.  

“One, we are still rebalancing employee counts from the over-hiring of the past decade,” said Hyoun Park, CEO and chief analyst of Amalgam Insights. “Tech companies were hiring with the assumption that they would grow at ridiculous rates that have not come to pass. Also, some tech companies think they can simply get rid of salespeople, especially in cash-cow industries where renewals seem to come in with little to no effort. Whether that is actually true or not, we are about to find out.”The job cuts may also signal concerns about the near-term revenue potential of AI, Park said. While Microsoft is under pressure to invest heavily in AI to sustain its stock valuation, it may be turning to short-term operating expense reductions to support its financial performance.

“The planned $80 billion investment in AI infrastructure is especially interesting because those numbers assume a massive number of people will adopt Microsoft-related AI products,” Park said. “Are 50 million+ people willing to pay an additional amount on Microsoft products to support AI? That is a massive bet that has been completely unjustified by the current AI market today.”Others point out that the company is betting on a long-term inflection in enterprise workload patterns driven by GenAI, but current adoption patterns remain volatile.

“Reports of Microsoft pausing or renegotiating data center leases reflect a prudent but necessary response to these uncertainties,” said Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research. “If workloads fail to scale or regulatory barriers increase, Microsoft, and by extension, other hyperscalers, could face underutilized infrastructure, prompting pricing recalibrations or service tier stratification.”

Changing sales environment

The focus on sales roles in the planned cuts is notable, with analysts saying it reflects a broader shift in how enterprise sales functions are evolving.

“The rise of AI copilots, telemetry-rich self-service portals, and data-driven journey mapping is reducing the need for large in-region sales teams,” Gogia said. “Microsoft’s realignment is part of a broader pattern also visible in Amazon, Google, and Salesforce.” However, while AI can personalize interactions at scale, it lacks the relational depth required in strategic deal-making, compliance negotiation, and multi-stakeholder orchestration, Gogia added.

Source:: Computer World

By Deepti Pathak Robotics has become a logistics game-changer, where speed and accuracy are paramount. Figure AI’s recent innovations…
The post Helix’s AI Humanoid Robots Are Reshaping Package Sorting appeared first on Fossbytes.

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By Hisan Kidwai Garena Free Fire Max is one of the most popular games on the planet, and for…
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After reports suggested Meta has tried to poach employees from OpenAI and Google Deepmind by offering huge compensation packages, OpenAI CEO Sam Altman weighed in, saying those reports are true. He confirmed them during a podcast with his brother Jack Altman.

“There have been huge offers to a lot of our team,” said Sam Altman, “like $100 million in sign-on bonuses, more than that in annual compensation.”

According to Altman, the recruitment attempts have largely failed. “I’m really glad that, at least so far, none of our best people have chosen to take it.

Sam Altman says he thinks it’s because employees have decided that OpenAI has a better chance of achieving artificial general intelligence, AGI, than Meta. It could also be because they believe that OpenAI could one day be a higher-valued company than Meta.

Source:: Computer World

Every Mac, iPhone, or iPad user should do everything they can to protect themselves against social engineering-based phishing attacks, a new report from Jamf warns. In a time of deep international tension, the digital threat environment reflects the zeitgeist, with hackers and attackers seeking out security weaknesses on a scale that continues to grow. 

Based on extensive research, the latest edition of Jamf’s annual Security 360 report looks at security trends on Apple’s mobile devices and on Macs. It notes that we’ve seen more than 500 CVE security warnings on macOS 15 since its launch, and more than 10 million phishing attacks in the last year. The report should be on the reading list of anyone concerned with managing Apple’s products at scale (or even at home).

Security begins at home

With phishing and social engineering, protecting personal devices is as important as protecting your business machines. According to Jamf, more than 90% of cyberattacks originate from social engineering attacks, many of which begin by targeting people where they live. Not only that, but up to 2% of all the 10 million phishing attacks the company identified are also classified as zero-day attacks — which means attacks are becoming dangerously sophisticated. 

This has become such a pervasive problem that Apple in 2024 actually published a support document explaining what you should look for to avoid social engineering attacks. Attackers are increasingly creative, pose as trusted entities, and will use a combination of personal information and AI to create convincing attacks. They recognize, after all, that it is not the attack you spot that gets you, it’s the one you miss.

Within this environment, it is important to note that 25% of organizations have been affected by a social engineering attack — even as 55% of mobile devices used at work run a vulnerable operating system and 32% of organizations still have at least one device with critical vulnerabilities in use across their stack. (The latter is a slight improvement on last year, but not much.)

The nature of what attackers want also seems to be changing. Jamf noticed that attempts to steal information are surging, accounting for 28% of all Mac malware, which suggests some degree of the surveillance taking place. These info-stealing attacks are replacing trojans as the biggest threat to Mac security. The environment is similar on iPhones and iPads, all of which are seeing a similar spike in exploit attempts, zero-day attacks, and convincing social-engineering-driven moves to weaponize digital trust.

The bottom line? While Apple’s platforms are secure by design, the applications you run or the people you interact with remain the biggest security weaknesses the platform has. Security on any platform is only as strong as the weakest link in the chain, even while attack attempts increase and become more convincing and complex. 

Defense is the best form of defense

Arnold Schwarzenegger allegedly believes that one should not complain about a situation unless you are prepared to try to do something to make it better. “If you see a problem and you don’t come to the table with apotential solution, I don’t want to hear your whining about how bad it is,” he says.

With that in mind, what can you as a reader do today to help address the growing scourge of Apple-focused malware? Here are some suggestions from Jamf:

Update devices to the latest software.

Protect devices with a passcode.

Use two-factor authentication and strong passwords to protect Apple accounts.

Install apps only from the App Store.

Use strong and unique passwords online.

Don’t click on links or attachments from unknown senders.

And, of course, don’t use older, unprotected operating systems or devices — certainly not when handling critical or confidential data.

Layer up, winter is coming

Organizations can build on these personal protections, of course. Apple devices need Apple-specific security solutions, including endpoint management solutions; enterprises should adopt device management; and they should prepare for the inevitable attacks by fostering a positive, blame-free culture for incident reporting and by eliminating inter-departmental siloes. Investment in staff training is important, too. 

It is also important to understand that in a hybrid, multi-platform, ultra mobile world there is no such thing as strict perimeter security anymore. That’s why it is essential to secure endpoints and implement zero-trust. It’s also why it is important to adopt a new posture toward security — there is no single form of effective security protection. At best, your business security relies on layers of protection that together form an effective and flexible security defense.

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Source:: Computer World

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