An AI usage treaty, negotiated by representatives of 57 countries, was unveiled Thursday, but its language is so overarching that it’s unclear if enterprise CIOs will need to do anything differently to comply.

This mostly European effort adds to a lengthy list of AI global compliance efforts on top of many new legal attempts to govern AI in the United States. The initial signatories were Andorra, Georgia, Iceland, Norway, the Republic of Moldova, San Marino, and the United Kingdom, as well as Israel, the United States of America, and the European Union.

In its announcement, the Council of Europe said, “there are serious risks and perils arising from certain activities within the lifecycle of artificial intelligence such as discrimination in a variety of contexts, gender inequality, the undermining of democratic processes, impairing human dignity or individual autonomy, or the misuses of artificial intelligence systems by some States for repressive purposes, in violation of international human rights law.”

What the treaty says

The treaty, dubbed Framework Convention on artificial intelligence and human rights, democracy, and the rule of law, did emphasize that companies must make it clear to users whether or not they are communicating with a human or an AI.

Companies under the treaty must give “notice that one is interacting with an artificial intelligence system and not with a human being” as well as “carry out risk and impact assessments in respect of actual and potential impacts on human rights, democracy and the rule of law.”

Entities must also document everything they can about AI usage and be ready to make it available to anyone who asks about it. The agreement says that entities must “document the relevant information regarding AI systems and their usage and to make it available to affected persons. The information must be sufficient to enable people concerned to challenge the decision(s) made through the use of the system or based substantially on it, and to challenge the use of the system itself” and to be able to “lodge a complaint to competent authorities.”

Double standard

One observer in the treaty negotiation process, Francesca Fanucci, a legal specialist at ECNL (European Center for Not-for-Profit Law Stichting), described the effort as having been “watered down”, mostly in dealing with private companies and national security. 

“The formulation of principles and obligations in this convention is so overbroad and fraught with caveats that it raises serious questions about their legal certainty and effective enforceability,” she told Reuters.

The final document does explicitly exclude national securities matters: “Matters relating to national defence do not fall within the scope of this Convention.”

In an interview with Computerworld, Fanucci said that the final version of the treaty treats businesses very differently than governments.

The treaty “establishes obligations for State Parties, not for private actors directly. This treaty imposes on the State Parties to apply its rules to the public sector, but to choose if and how to apply them in their national legislation to the private sector. This is a compromise reached with the countries who specifically asked to have the private sector excluded, among these were the US, Canada, Israel and the UK,” Fanucci said. “They are practically allowed to place a reservation to the treaty.”

“This double standard is disappointing,” she added.

Lack of specifics

Tim Peters, an officer of compliance firm Enghouse Systems in Canada, was one of many who applauded the idea and intent of the treaty while questioning its specifics.

“The Council of Europe’s AI treaty is a well-intentioned but fundamentally flawed attempt to regulate a rapidly evolving space with yesterday’s tools. Although the treaty touts itself as technology-neutral, this neutrality may be its Achilles’ heel,” Peters said. “AI is not a one-size-fits-all solution, and attempting to apply blanket rules that govern everything from customer service bots to autonomous weapons could stifle innovation and push Europe into a regulatory straitjacket.”

Peters added that this could ultimately undermine enterprise AI efforts. 

“Enterprise IT executives should be concerned about the unintended consequences: stifling their ability to adapt, slowing down AI development, and driving talent and investment to more AI-friendly regions,” Peters said. “Ultimately, this treaty could create a competitive divide between companies playing it safe in Europe and those pushing boundaries elsewhere. Enterprises that want to thrive need to think critically about the long-term impact of this treaty, not just on AI ethics, but on their ability to innovate.”

Another industry executive, Trustible CTO Andrew Gamino-Cheong, also questioned the agreement’s lack of specifics.

“The actual contents of the treaty aren’t particularly strong and are mostly high level statements of principles. But I think it’s mostly an effort for countries to unify in asserting their rights as sovereign entities over the digital world. For some context on what I mean, I see what’s happening with Elon Musk and Brazil as a good example of the challenges governments face with tech,” Gamino-Cheong said. “It is technologically difficult to block Starlink in Brazil, which can in turn allow access to X, which is able to set its own content rules and dodge what Brazil wants them to do. Similarly, even though Clearview AI doesn’t legally operate in the EU, their having EU citizens’ data is enough for GDPR lawsuits against them there.”

Ernst & Young managing director Brian Levine addressed questions about the enforceability of this treaty, especially with companies in the United States, even though the US was one of the signatories. It is not uncommon for American companies to ignore European fines and penalties. 

“One step at a time. You can’t enforce shared rules and norms until you first reach agreement on what the rules and norms are,” Levine said. “We are rapidly exiting the ‘Wild West’ phase of AI. Get ready for the shift from too little regulation and guidance to too much.”

The treaty will enter into force “on the first day of the month following the expiration of a period of three months after the date on which five signatories, including at least three Council of Europe member states, have ratified it,” the announcement said. 

Generative AI (genAI) features added to an existing Apple Watch health app may light the path toward personalized and data-led healthcare for patients with Parkinson’s disease. The StrivePD app is made by Rune Labs, a California-based entity focused on delivering next-generation care for people with neurological disorders.

StrivePD has been enhanced with new genAI-created clinical reporting tools that provide in-depth data on a patient and the progression of their disease, and it delivers personalized educational content to patients, caregivers, and clinicians to improve outcomes.

What is StrivePD and how does it help?

The reports, allegedly HIPAA-compliant and shared with patients via email, are structured so patients get good insight into where they are with the disease, including summaries of their medication compliance, exercise, and symptom fluctuations. The app also delivers coaching in the form of exercise suggestions and tips around sleep patterns, and draws on data gathered by the Apple Watch (along with information shared by the patient).

In theory, the combined solution should help patients while also equipping medical professionals with deeper information they can use to guide treatment. 

It could even enable Parkinson’s patients to access care in the first place “The unfortunate reality is there is a structural shortage of specialists who can treat Parkinson’s, and the problem is getting worse,” said Rune Labs CEO Brian Pepin. “Most Parkinson’s patients struggle to get adequate access to care.”

Changing lives, one focused LLM at a time

It should be noted that the Rune Labs solution was in 2022 given the go ahead by the US Food and Drug Administration (FDA) to collect patient symptom data through measurements made by Apple Watch.

This makes it a recognized solution that could in the future become a poster child for the potential of genAI to deliver life-changing health benefits when deployed in such focused domains. (Turns out there’s a lot more to genAI than automating job applications and creating amusing images — data analysis at this level could yield profound benefits in terms of healthcare results and patient autonomy.)

Apple should be looking at this

I’d be very, very surprised if Apple’s health teams were not themselves already exploring ways in which to combine the data gathered by their own sensors and services with focused large language models (LLMs) to provide similar benefits. It’s a natural progression from the accurate exercise tracking tools the company has already deployed, including but not limited to swimming and wheelchair activity sensors.

The existence of that kind of highly personalized data and the also existing connection between Apple’s devices and patient medical data opens up interesting possibilities for LLM-augmented health and services that extend beyond Apple Fitness.

In that sense, the Rune Labs announcement could prophesize future health-related services that combine genAI with the vast quantity of personal data Apple’s ecosystem already gathers.

What’s happening in Apple R&D?

Apple CEO Tim Cook has frequently claimed that Apple will in the end be remembered for the work it is doing in health. Given the entire company is now shoulders to the wheel in the push to put AI in everything, it is unlikely its health teams aren’t at least trying to book some internal R&D time to explore how it can be applied in that sector.

If the Rune Labs solution actually delivers on its promises, Apple’s health teams will at least have an argument to justify that investment. But Apple aside, tools like these that empower better patient care and encourage personal autonomy are among the bright spots for a technology so many people fear may be a dystopian fin de siècle. 

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The UK’s antitrust regulator has concluded its investigation into Microsoft’s hiring of the majority of staff from Inflection and its licensing of the company’s technology.

The Competition and Markets Authority (CMA) published a summary of its decision Wednesday, finding that while Microsoft’s actions constituted a “relevant merger situation” and thus fall under its purview, they did not result in what it called “a realistic prospect of a substantial lessening of competition (SLC).”

In other words, the deal — which didn’t involve Microsoft buying the company — is a merger, but the regulator is OK with that.

This means that the CMA will not pursue a full-scale investigation into the deal, which poured an estimated US$650 million into Inflection’s coffers.

Not this time, anyway: Similar deals may, however, come under scrutiny for their effect on competition.

This was one of many regulatory looks at investments in AI startups by big tech companies hoping to escape regulatory scrutiny with what some have dubbed a quasi-merger: strategic investments and/or hiring key team members that gain the investor influence or control over the startup without actually buying the company.

At the same time the UK investigation into Microsoft was announced, the US Federal Trade Commission (FTC) began a look into Amazon’s hiring of key executives, including the CEO, from AI startup Adept, and its plan to license some of Adept’s technology. And in early August, the CMA announced that it is launching an inquiry into Amazon’s relationship with Anthropic to determine whether it, too, warrants a full investigation. A CMA inquiry into Google’s relationship with Anthropic is also underway.

When is a merger not a merger?

In its summary of the Microsoft-Inflection decision, the CMA said that that it assessed the criteria for a relevant merger situation under the Enterprise Act 2022, noting, “There is no particular combination of assets that constitutes an enterprise. As set out in the CMA’s guidance, it may include a group of employees and their know-how where this enables a particular business activity to be continued.”

Furthermore, it said, “In addition to hiring the core former Inflection team, Microsoft also acquired additional assets, including access to Inflection IP. The combination of acquiring the core team together with these assets was key to the value of the Transaction, as it enabled the former Inflection team to continue the pre-Transaction Inflection roadmap for consumer-facing AI product development within Microsoft.

“On this basis, the CMA believes that Microsoft has substantively acquired Inflection’s pre-Transaction FM [Foundation model] and chatbot development capabilities. Accordingly, the CMA has found that at least part of the activities of pre-Transaction Inflection has been brought under the control of Microsoft and, as a result, that two enterprises have ceased to be distinct such that the Transaction falls within the CMA’s merger control jurisdiction for review.”

The CMA said that the full text of its decision will be published “shortly” on the web page for the case.

Anthropic has launched the Claude Enterprise subscription plan, enabling businesses to securely leverage their own corporate data in their interactions with its Claude large language model. It’s a complement to Claude Work, Anthropic’s product aimed at small organizations, and a competitor for OpenAI’s ChatGPT Enterprise, released last year.

“The goal for us, for Claude Work and Claude for Enterprise, is really to enable and empower every team within an enterprise so that you can really become the most creative and most productive version of yourself,” said Nicholas Lin, Claude Enterprise product lead, in an interview.

Claude Enterprise features an expanded context window — 500,000 tokens, more than double the 200,000 previously offered — which Anthropic said is the equivalent of hundreds of sales transcripts, dozens of 100+ page documents, or 200,000 lines of code.

Dynamic workspaces

“Artifacts” — dynamic workspaces that, Lin said, let users “really see what’s going on in Claude’s head and to really iterate on outputs with Claude” — will assist users in creating data visualizations, documentation, presentations, and more.

“One thing I love to use artifacts for is a great way to just brainstorm with Claude, and using Claude to think about drawing diagrams and helping it visualize concepts,” he said. For example, a marketer could create an artifact in the form of a marketing calendar for a campaign, or generate content for the campaign, or a strategy document. In sales, Claude could analyze sales data, forecast trends, and generate collateral for a sales meeting.

The activity feed, he said, lets users draw inspiration from others in their organization. “Activity feed really enables you and others around you in the organization to share the most insightful pieces of feedback that you’re working with Claude on, so this is pieces of knowledge insights from your conversations with Claude in artifact outputs through the organization,” he said.

And, since manually uploading data is not sustainable at scale, the company is introducing native data integrations. The first, with GitHub, is now in public beta.

“We want to make sure that Claude is really well integrated into your everyday workflow,” Lin said. “This is the first of our native integrations. Many more will be coming in the coming months, and this is also the first of our software developer focused features. Many more will be also coming in the coming months.”

And, he promised, the uploaded data will not be used to train models.

Granular permissions

Anthropic says that, along with its AI features, Claude Enterprise contains enterprise-grade security controls including single sign-on (SSO) and domain capture, and role-based access with granular permissioning. Within a few weeks, Lin said, audit logs for security and compliance monitoring, and automated user provisioning and access control, known as the System for Cross-domain Identity Management (SCIM), will be available as well.

These features are long overdue, said Jeremy Roberts, senior research director at Info-Tech Research Group.

“It’s high time we got some general-purpose AI SaaS to compete with the likes of Microsoft Copilot,” he said. “When we think about new software, we focus a lot on its capabilities, but to be an enterprise solution, it must integrate nicely into the broader ecosystem. The announcements around SSO, RBAC, and audit logs are essential for this. Anyone worried about consumer technology in their businesses should be greatly heartened by the increasing competition in this space.”

Another analyst is curious whether the user experience will surpass those of other AI products.

“I’m excited to see the release of the Enterprise version of Anthropic,” said Terra Higginson, principal research director at Info-Tech Research Group. “Just like we saw in the search engine race of the early 2000s, the product with the best user experience and functionality dominated. Will Claude by Anthropic be the winner of the LLM race? Many of these systems are still offering subpar user experiences, and, to make matters even worse, the companies put a ton of restrictions that just make users lean towards private alternatives.”

Claude Enterprise is available today. Pricing was not announced; Lin said that each organization will be given a customized price based on its needs.

Intel’s plunging stock price, which as of noon New York time on Tuesday was the lowest it has been since 2010, could cost the chip giant its coveted spot on the Dow Jones Industrial Average (DJIA).

It comes at a very difficult time for Intel, as it is trying to maintain its enterprise relevance in the face of more effective generative artificial intelligence (genAI) campaigns from the likes of Nvidia.

Reuters reported that Intel, which was the second technology company to join the DJIA in the late 1990s, was “likely to be removed from the Dow” because of a “near 60% decline in the company’s shares this year that has made it the worst performer on the index and left it with the lowest stock price on the price-weighted Dow.”

Analysts and financial observers were mixed on the ultimate implications for enterprise IT executives. On the one hand, Intel’s installed enterprise base is so huge that it is not likely to face any imminent danger. That gives Intel a couple of years to turn things around.

But genAI is the perception problem. If they are seen as lagging in that space, that perception could hurt them severely.

However Ryan Shrout, president of Signal65, thinks Intel’s huge installed base will provide a buffer. He spent almost five years at Intel before departing in September 2023, with his final role being Intel’s senior director for client segment strategy in the graphics and AI group.

“Even though Intel appears to be so far behind in the world of technology based on their earnings report and the race versus Nvidia in the AI space, you have to keep in mind that something like 80% of the client market — laptops and PCs — use Intel chips,” Shrout said. “Even in the data center CPU space, 70% or so are using Intel Xeon processors. If Intel disappeared tomorrow, nobody has the capacity to fill that gap.”

But Shrout echoed analysts and pointed to AI strategy, or at least the perception of that strategy, as the overwhelming cause of Intel’s current difficulties. 

“The competition that’s come into the market was allowed to come in because Intel didn’t see the writing on the wall for the AI movement. That’s a self-inflicted blind spot,” Shrout said. 

Intel has taken various steps to try and strengthen its financial numbers, such as recently having suspended its dividend and laying off about 15% of its employees, along with splitting its foundry operations from its design teams. 

“Intel CEO Pat Gelsinger and key executives are expected to present a plan later this month to the company’s board of directors to slice off unnecessary businesses and revamp capital spending,” said a Reuters report. “The plan will include ideas on how to shave overall costs by selling businesses, including its programmable chip unit Altera, that Intel can no longer afford to fund from the company’s once-sizeable profit.”

Forrester senior analyst Alvin Nguyen, who oversees their Intel coverage, said that he is still a fan of Intel’s long term strategy, but he sees various problems with their execution.

“Foundry is very expensive. It’s capital intensive,” Nguyen said. “They have made a big bet on the foundry business. If it works, they will have the best semiconductor fab process [in the industry]. If they win the foundry battle, people will look at them differently.”

Some have questioned whether Intel was wrong to decline to invest in OpenAI, but Nguyen said that he thinks it might have been the right decision for Intel. Indeed, he saId, “I am wondering if Microsoft today is questioning the wisdom of their decision [to invest in OpenAI].”

Nguyen added that Intel’s “push towards AI everywhere seems like a smart bet.” He added that Intel’s lack of position within mobile and IoT devices is a problem.

As for the prospect of Intel being removed from the DJIA, Nguyen doubted it would make much of an impact. “It’s just a status symbol. If they lose their Dow status, it’s more of a reputational hit than anything else,” he said.

Nguyen agreed with Shrout that Intel’s massive current installed base will insulate the company for at least a couple of years, giving them time to turn things around. 

“Intel is still in danger and the more hits they take, the worse their position,” Nguyen said.

Another Intel industry analyst is Mario Morales, the IDC group vice president for semiconductors and enabling technologies. 

“There is an ongoing battle for survival at Intel,” Morales said, adding that he thinks that splitting the company and selling off divisions may be the best move. “The parts of Intel are more valuable as pieces than as a whole.”

Morales’ sources have reported that Intel is “actively talking with more than 100 customers, but none of them have yet committed” to more major purchases, he said.

A critical problem for Intel in the perception realm is that they have been outsourcing too much; the manufacturing of both its Lunar Lake and Arrow Lake CPUs were almost entirely outsourced to Taiwan Semiconductor Manufacturing Company Limited (TSMC).

“Even Intel’s own products are being built somewhere else,” Morales said, suggesting that such a move is sending the wrong message to enterprise CIOs. This is happening just as those executives are thinking about creating their own on-prem operations for genAI deployments, in an attempt to gain more control than they now have in the cloud.

“Intel has always had a lot of technology that can enable genAI. They simply had the wrong product mix,” Morales said. As the industry moved from CPUs to GPUs, Intel didn’t move quickly enough, he said.

On an optimistic note, Morales said that there is industry precedent for exactly such a turnaround. Some ten years, AMD faced similar issues and overcame them.

“In 2014, AMD was a month or two away from bankruptcy,” Morales said, stressing that “because AMD was so close to death,” its CEO halted a wide range of side projects that were not central to their customers. 

“Intel has to suffer the tough pill [and decide that] ‘If we can’t lead (in a segment), then we can’t be in those spaces,’” Morales said. “It is well beyond a wakeup call. They are already late.”

In another interesting move that hints at a symbiotic relationship, ChatGPT maker OpenAI has reportedly followed Apple to become a lead customer for TSMC processors. Given the industry lead Apple has achieved with Apple Silicon, the move could be seen as tacit enthusiasm, rather than symbiosis, but follows reports Apple might stake an investment in OpenAI.

These moves by the biggest names in tech underscore the profound difference generative AI (genAI) has made in artificial intelligence, which has taken what’s been part of the industry for decades and placed it at the forefront of the zeitgeist. That Open AI plans to work with TSMC can also be seen as justification of the integrity of Apple’s approach to silicon design, as it concedes the computational power these processors provide while meeting real world needs in terms of energy supply.

The first OpenAI chips under the purported deal are set to slip off the lines some time in 2026.

A new platform battle?

As Apple stands at the cusp of becoming the world’s biggest multi-platform AI ecosystem, the move also hints at new competition down the road.  After all, it was only earlier this year that OpenAI CEO Sam Altman was reported to be getting into chip manufacturing. Now, the company has booked into early production of chips using TSMC’s A16 process, which are expected to enter production in 2026. 

Despite using the same foundry, the processors won’t be the same as Apple’s and will be designed apparently by Broadcom and Marvell.

While it is very possible that OpenAI wants to use its chips inside its own servers, it is also plausible it might also have plans to introduce its own devices, or to offer up its AI inside chips as options to other computer hardware manufacturers.

It takes energy to make things happen

Everyone with a passing interest in genAI recognizes that the scale of energy consumption required to deliver server-based services using the tech is very, very high. Even at this point in genAI deployment, the energy being used is higher than that required by some smaller nations — and those demands will only increase.

With that in mind, Apple’s M-series chip message around computational performance per watt turns out to be even more prescient than earlier believed. After all, if genAI is to be woven into global use, it must meet those needs without using all the world’s energy; reducing energy demands is mandatory. This also implies tech firms will continue to make major investments in renewable energy supply to drive those server farms, and suggests the carbon offset market will be forced to prove its legitimacy, rather than continuing to be a kind of 21st century equivalent of Papal Indulgences (as George Monbiot once described it).

Power, profit, people

The chips Apple makes deliver excellent computational performance at significantly less power than rival processors. Once Apple’s production moves to TSMC’s A16 process, you’ll see another 8-10% spike in performance for up to 20% less power, a report claims.

That’s great for Mac, iPad, and iPhone users — who doesn’t want more powerful devices that use less energy? But for server-based services handling millions of requests daily, that power difference affects both environmental performance and operational costs in terms of energy bills.

With that in mind, OpenAI doesn’t need to be looking to become a hardware competitor to unlock value from chip design; its own running costs will be reduced dramatically through the introduction of more efficient chips — particularly as the number of people it serves grows from millions to billions.

While people in tech might see AI everywhere, most people haven’t begun using genAI tools and services just yet — something which is going to change within the next few weeks as Apple ships its AI-ready devices, starting with the next iPhone.

But if the direction of travel is anything to go by — a trajectory in which Apple and Microsoft seem set on investing in a company that could yet compete with both of them — it seems the people at the summit of Tech Power Mountain don’t merely see OpenAI as a service provider, but as a peer player in the future of IT. We just have to hope that neither they, nor the AI, are hallucinating.

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