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První paměťový čip vyráběný „jednociferným“ procesem je na světě. Funkční DRAM postavená na technologii Vertical Channel Transistor ukazuje technologické směřování nadcházející generace pamětí…

Od 28. prosince 2024 v EU platí nařízení, podle něhož výrobci nesmí uvádět na trh nové mobily, foťáky, handheldové konzole, sluchátka, myši, klávesnice a další bezdrátová zařízení bez konektoru USB-C. Týká se to všech, které nějaký nabíjecí konektor nabízejí. Pokud mají jen bezdrátové nabíjení nebo ...

Tim Cook’s impending retirement as Apple’s CEO marks the end of an era — the years  when the Apple-versus-Microsoft fight dominated the tech world.

Of course, it’s been a long time since those two companies ruled by themselves. These days, Google, Meta, OpenAI, Anthropic and Amazon are just as influential. Still, Cook’s decision to step down as Apple CEO on Sept. 1 to become chairman of Apple’s board is a good time to revisit the debate: who’s the better leader, Cook or Microsoft CEO Satya Nadella?

Both men faced the unenviable task of replacing larger-than-life company founders and visionaries. Cook took over as CEO at Apple in August 2011, two months before Steve Jobs died. Nadella ascended to the top job at Microsoft in February 2014 after Steve Ballmer stepped down. (Ballmer had replaced founder Bill Gates as CEO in 2000.)

To determine who’s been a better leader — and positioned their companies better for future success — we need to look at the challenges each faced as CEO.

Cook’s and Nadella’s biggest challenges

In the 10 years before Cook took over at Apple, the company saw an unprecedented run of innovation under Jobs, creating products that redefined technology – not only what it could do but also shaping the way people live and work.

The iPod in 2001 launched the digital music revolution. That was followed two years later by iTunes, which completed Apple’s dominance in digital music. The iPhone in 2007 single-handedly created the mobile revolution, along with the follow-on App Store in 2008. That same year, Apple launched the iPad. Then, in May 2011, Jobs unveiled iCloud.

Cook’s two greatest challenges when he took over: make as much money as possible from Jobs’ innovations and continue to create groundbreaking products.

Nadella took over at Microsoft during what has been called the company’s “lost decade.” Quite simply the company had stagnated, launching no new significant products while milking its cash cow, Windows, as much as it could.

In that decade Microsoft couldn’t even handle Windows properly. Windows Vista, launched in 2007, is generally regarded as the worst version of Windows ever. And in  2012, Microsoft released Windows 8, also considered a big miss.

It’s said that, to a man with a hammer, the entire world looks like a nail. The same could be said about Ballmer and Windows: he saw it as the solution to every tech problem that existed. (Gates, by then board chairman, agreed.)

That myopic view led to several disasters, most notably missing out on the mobile phone revolution — even though Microsoft had in 2003 launched Windows Mobile, a smartphone operating system, well before Apple.

Nadella’s greatest challenges were legion: create innovative products, pivot away from Windows, and fix a toxic company culture that had executives spending their energy on turf battles.

How Cook has fared at Apple

By any measure, Cook has been a superb technocratic leader at Apple. His big achievements were in the behind-the-scenes nuts-and-bolts of manufacturing that don’t make headlines, but that helped Apple cash in on Jobs’ many innovations and become a multi-trillion-dollar company.

Most important, he transformed Apple’s supply chain. It was a complicated mess when Cook took over as CEO. He streamlined things by reducing the number of suppliers and manufacturers Apple dealt with. He also put into effect a “just-in-time” delivery of components that the company needed, reducing costs and making the manufacturing process more efficient and more nimble in responding to a fast-changing market.

He also recognized the value of services, transforming iCloud, Apple Music, the App Store, and Apple Pay into financial juggernauts, and rolling out Apple TV+ to critical acclaim. But Cook never succeeded in developing breakthroughs like the iPhone. The Apple Watch has been a hit, but it didn’t change the tech world in the way many of Jobs’ products did. (The jury is still out on the Vision Pro.)

Cook also completely missed out on AI. Apple is so far behind in that area at the moment you can’t even count the company as an also-ran. And that might spell trouble for the future. Making money from aging technologies might not be enough for Apple to remain dominant in the coming years when AI will be king.

Nadella’s tenure at Microsoft

Everyone knew Microsoft was getting a Cook-style technocrat when Nadella became CEO. What surprised everyone — including me — was that it got one of tech’s great visionaries as well.

Nadella took over a moribund company and accomplished one of tech’s greatest turnarounds. He put an end to the company’s divisive culture, de-emphasized the over reliance on Windows, increased its cloud presence, and killed Windows Phone, which had cost the company billions and remained a drag on its success.

Eventually, he reorganized the company to make it cloud-centric rather than Windows-centric, getting rid of a number of problematic executives, including Terry Myerson, who had been executive vice president of its Windows and devices business. Microsoft became a cloud company more than an operating system company.

He also forged a better relationship with customers. Rather than try to ram Windows down their throats at every opportunity, as Gates and Ballmer did, he embraced making Microsoft technology work with competing products. For example, he allowed Linux to run  SQL Server. He also bought the developer platform GitHub, and let it remain open and independent rather than become Microsoft-focused.

Then along came AI. Nadella recognized AI was the future, and by investing in OpenAI, forging relationships with other AI companies including Anthropic, and building an internal powerhouse of AI development, Microsoft became one of the world’s foremost AI companies.

The winner

So who’s been the better CEO? 

Cook took over a company with a wealth of ground-breaking products that had created entirely new markets, and did a great job of milking them for all they were worth. He’s certainly been great at making money for Apple. But he’s leaving behind a company that despite its profitability, faces a problematic future in an AI-first world.

Nadella took over a company whose innovative days were far behind it, rebuilt it from the ground up, killed off money-losing tech like Windows Phone, de-emphasized Windows, and then organized the company around the cloud.

In the last few years, he recognized the potential of AI and has been organizing the company around that. Microsoft is better positioned for the AI future than Apple. 

For those reasons, Nadella comes out on top. 

Philips ukazuje, že dobrý OLED nemusí stát na extrémech. Nesnaží se ohromit maximálním jasem ani efektními triky, ale sází na vyvážený obraz, přesné barvy a podporu všech HDR formátů. Přidává Ambilight, který reálně mění zážitek ze sledování, a dohromady tak vzniká televizor, který dává smysl v ...

Thirty ClawHub skills published by a single author are silently co-opting AI agents and creating a mass cryptocurrency mining swarm – without any malware or user consent. Agentic AI security outfit Manifold's research lead Ax Sharma spotted the skills on ClawHub, a registry and marketplace for OpenClaw skills. A ClawHub user who goes by "imaflytok" published the skills, which have scored around 9,800 downloads. Sharma told The Register that this campaign – he calls it “ClawSwarm” – differs from past efforts to distribute malicious ClawHub code because it doesn’t use malware or target humans. Instead, ClawSwarm targets the agents themselves and SKILL.md files, documents that give agents instructions on how to interact with other systems. "ClawSwarm isn't a vulnerability disclosure," Sharma told us. "There's no flaw to patch and nothing covert about the infrastructure. It's an open source project on GitHub with public docs, a Telegram group, and a token on a public chain." The campaign sees a user install a seemingly benign skill – these purport to be everything from a cron helper (903 downloads) to an Agent Security skill (685 downloads), a whale watcher (347 downloads), a cross-platform poster (292 downloads), and a predictions market integration (154 downloads). The AI agent then registers itself at "onlyflies.buzz," a site that centers around $FLY tokens and "provocative" art. After registering itself with the external server, the agent follows the instructions in a SKILL.md file and therefore reports its name and capabilities to the third-party, along with what skills it has installed. The agent stores credentials on disk, checks in every four hours, and assuming the right skills are installed, it generates a Hedera crypto wallet and registers the private key with the same server. The human user doesn't approve any of this activity and doesn’t see it happening. In addition to being the name of the crypto-swarm campaign Sharma documented, ClawSwarm is also an open source agentic skill framework on GitHub. The imaflytok's skills open at onlyflies.buzz are one such implementation of that framework. "You can read all of this and conclude it's a small crypto community building agent infrastructure. Maybe it is," Sharma wrote. "But the mechanism is identical regardless of intent: an AI agent silently registering with a third party server, reporting its capabilities, generating crypto keys, and accepting remote tasks – all without the user initiating or approving any of it." It's similar to the earlier Tea Protocol token farming campaigns, in which more than 150,000 spammy packages flooded the npm registry to farm Tea points. ClawSwarm, according to Sharma, "follows the same playbook," but uses skills instead of npm packages. "Whether ClawSwarm instances are a legitimate experiment in agent economics or a recruitment funnel for speculative crypto, the result for the user is the same: their agent is doing things they didn't ask it to do, for someone they don't know, with keys they didn't authorize," he wrote. ClawHub maintainers did not immediately respond to The Register's inquiries, nor did the legitimate ClawSwarm open source framework. Sharma says maintainers are in a tough position because it's not really a security problem, despite agents joining a network and generating wallets without their human user's approval. "The registry layer is the wrong place to solve this," he told The Register. "A scanner looking for malicious code patterns finds nothing: the cURL calls are clean, the SDK is legitimate. What's needed is runtime visibility into what agents actually do once a skill is installed. Registries could require disclosure of network endpoints and wallet generation in skill manifests, but that's a policy question, not a security one." ®

Yet another reason not to feast on OpenClaw

Thirty ClawHub skills published by a single author are silently co-opting AI agents and creating a mass cryptocurrency mining swarm – without any malware or user consent.…

Evropa nevzdává snahu vyslat na Mars svůj první rover • Rosalind Franklin má odstartovat v roce 2028 na vrcholu rakety Falcon Heavy • Projektu se účastnilo i Rusko, ale po invazi na Ukrajinu došlo k ukončení spolupráce

Navzdory zprávám o zdražování ceny procesorů Ryzen nadále klesají. Cena Ryzen 9 9950X3D o téměř $80, ale více či méně levnější jsou téměř všechny modely. Akce na Ryzen 7 7800X3D srazila cenu o $75…

In yet another instance of threat actors quickly jumping on the exploitation bandwagon, a newly disclosed critical security flaw in BerriAI's LiteLLM Python package has come under active exploitation in the wild within 36 hours of the bug becoming public knowledge. The vulnerability, tracked as CVE-2026-42208 (CVSS score: 9.3), is an SQL injection that could be exploited to modify the underlying

In yet another instance of threat actors quickly jumping on the exploitation bandwagon, a newly disclosed critical security flaw in BerriAI's LiteLLM Python package has come under active exploitation in the wild within 36 hours of the bug becoming public knowledge. The vulnerability, tracked as CVE-2026-42208 (CVSS score: 9.3), is an SQL injection that could be exploited to modify the underlyingRavie Lakshmananhttp://www.blogger.com/profile/[email protected]

Vývojáři svobodného 3D softwaru Blender představili (𝕏, Mastodon, Bluesky) nejnovějšího firemního sponzora Blenderu. Je ním společnost Anthropic stojící za AI Claude a úroveň sponzoringu je Patron, tj. minimálně 240 tisíc eur ročně. Anthropic oznámil sponzorství v tiskové zprávě Claude for Creative Work.

AWS on Tuesday announced an expansion of its partnership with OpenAI and launched a major new agentic AI push with the introduction of a new desktop app for Amazon Quick, a personal AI assistant, and an expansion of Amazon Connect from a single product into four distinct offerings.

News of the enhanced partnership comes 24 hours after OpenAI and Microsoft stated they were changing their contract terms and revising certain exclusivity and revenue sharing conditions.

OpenAI’s agreement with AWS will see the latest OpenAI models, as well as its Codex coding agent, available on Amazon Bedrock, and the addition of new Amazon Bedrock Managed Agents, an AI agent builder for cloud environments powered by OpenAI.

Amazon Connect is being expanded, and will now include Amazon Connect Decisions, Amazon Connect Talent, Amazon Connect Customer, and Amazon Connect Health.

Colleen Aubrey, SVP of applied AI solutions at AWS, wrote in a blog post that the four Connect components “draw on our expertise incorporating agents throughout Amazon’s operations.”

30 years of operational expertise

Igor Ikonnikov, advisory fellow at Info-Tech Research Group, said, “the switching from generic AI-powered solutions to purpose-built and trained AI agents is a common trend, and a good one.”

Having specialized AI solutions, he said, “would increase their reliability and facilitate their adoption. If an AI agent has a well-defined role and feature set, it is easier to onboard it as a new teammate. The quality of the build and the expertise used in model training would be the differentiating factors.”

From this perspective, Ikonnikov said, “Amazon Connect Decisions seems to be an attractive supply chain management solution, as it is built on 30 years of Amazon operational expertise in handling hundreds of millions of SKUs coming from millions of suppliers from all over the world. Another important promise [from AWS]: AI agents comprising Connect Decisions ‘provide complete visibility and transparency into AI recommendations and decision-making,’ something highly commendable (too good to be true, though; I’d like to see it in action).”

The same, pointed out Ikonnikov, “would apply to Amazon Connect Customer. It has already been used for years by State Farm, Air Canada, and US Bank, with an impressive scale, complexity, and diversity of customer-oriented solutions.”

Amazon Connect Talent, he added, “is also based on impressive scale and expertise; Amazon claims to have hired 250,000 seasonal employees in 2025 alone. The problem with this specialized solution lies outside of Amazon’s control, but in the nature of the domain, where job applications could be tweaked to fit job requirements and now could also be auto-generated by other AI-powered software.”

Thus, it’s not just scale and expertise in dealing with humans that matter, but the new expertise of dealing with outside AI submitting job applications, said Ikonnikov.

Amazon Connect Health, he said, “is also backed by Amazon’s existing offerings, One Medical and Amazon Pharmacy. The concern about this AI agent stems from the sensitive nature of the health care data and security enforcement around its use, as well as the Connect Health Agent behaviour. It would require a mature control plane, something stricter and more police-like than Bedrock Agent Runtime.”

Turning questions into answers

In addition, AWS predicted in in a release that the Amazon Quick desktop app will “enable a rapid evolution of AI in the workplace. When AI knows you, your team, and your company, it can become an intelligent assistant that turns questions into answers, answers into actions, and actions into outcomes.”

Shashi Bellamkonda, principal research director at Info-Tech Research Group, said, “Amazon is filling a gap that it had with consumer-facing AI. Although they had several Nova models that an AWS user can access, it was on similar lines with Gemini and Claude, but very techie if you wanted to connect to Bedrock and create more functionality.”

He said, “[I am] happy to see that users won’t need an AWS account with Quick Assistant. It can potentially act as a substitute for Claude on the desktop, and if implemented well (and is, as Amazon claims, ‘proactive, has context, does work for you, and learns you over time,’), it can be powerful for both consumers and enterprises offering this to their teams.”

Bellamkonda pointed out, “we all need an agent, and even if Quick Assistant does not displace Claude, Amazon as an investor in Anthropic still benefits. They could potentially displace Microsoft Copilot and ChatGPT and be blessed by IT and security teams. Amazon will have to think user-friendly versus tech-expert audience.”

This is, he said, “a big move by Amazon, from being thought of as an AI platform infrastructure to an AI assistant product that can be used by a larger audience. This could help increase the number of customers who will move to Bedrock as they get familiar with AWS AI products.”

CIOs and CSOs, added Bellamkonda, “will create a sandbox to test this desktop, which listens to and ingests all interactions before introducing it across the enterprise. Amazon showed a large enterprise already using it. For individual users, it will take time for them to adopt this. I have no doubt about the power of this agent. I just wish Amazon made it easier in the last mile for non-tech users.”

VNC server wayvnc pro Wayland kompozitory postavené nad wlroots - ne GNOME, KDE nebo Weston - byl vydán ve verzi 0.10.0. Vydána byla také verze 1.0.0 související knihovny neatvnc.

Enterprises are quickly moving from AI experimentation to deployment, however, when agentic AI begins making more decisions, invoking more tools, and operating across fragmented data environments, there can be an erosion of visibility, governance, and trust.

SAS laid out its answer to that problem at its annual conference, SAS Innovate, introducing a new family of copilots, agent frameworks, Model Context Protocol (MCP) plugins, and management tools to help enterprises operationalize AI without losing control of it.

“What we’re seeing here is really a shift from AI that forms to AI that acts,” Marinela Profi, the company’s global AI and generative AI market strategy lead, said at the event. “This is a significant leap, because it introduces new requirements around trust, around governance, around accountability.”

Interacting with agents more intuitively

To begin with, SAS today announced SAS Viya Copilot, a human-governed, conversational AI assistant embedded into its Viya platform. It integrates Microsoft Foundry, operating within analytics workflows to help developers, data scientists, and other users instructing it in natural language to analyze data, build models, and make decisions across workflows.

“You have an expert assistant that allows you to take actions, ask questions, and help you navigate across the full analytical lifecycle,” Profi explained.

Its capabilities include: General Q&A across core Viya applications; production of documented and explainable AI-generated code; model pipeline guidance including recommendations and next steps; conversational dashboarding; and visual investigation with AI-assisted search and alert narratives. Copilot capabilities will eventually extend to data management, model management, and AI infrastructure, according to SAS. 

The company is initially launching two Copilots: Asset and Liability Management (ALM), for developing scenarios, executing and interpreting financial risk workflows, and translating natural language inputs into analytic models; and Health Clinical Data Discovery, for analyzing data, creating cohorts, and investigating research papers and other medical documents.

SAS plans to expand Viya Copilot into additional industries, including banking and manufacturing, later this year.

Going beyond embedded AI assistants, SAS is providing tools and infrastructure to connect and govern internal and external agents. The new SAS Viya MCP server standardizes connections so external agents can safely access SAS tools, data, and models, using the large language model (LLM) or interface of their choice (Claude, GPT, Gemini), without having to create custom integrations, duplicate logic, or bypass controls.

“The Copilot is not only answering questions for you, it can invoke capabilities across Viya in a more structured way,” Profi said.

In addition, a new Agentic AI Accelerator provides a collection of code, interfaces, components, and best practices that allow teams across skill levels (developers, low-code or no-code users) to design, build, deploy, and manage agents within SAS Viya, she explained.

Current Viya users can access both the MCP server and AI Accelerator via GitHub.

Maintaining human judgment

SAS continues to emphasize the importance of oversight, trustworthy AI, and human-in-the-loop control.

Furthering this mission, the company is introducing SAS AI Navigator. The Software-as-a-Service (SaaS) tool helps enterprises inventory, govern, and apply policies to underlying AI models.

Available in Q3 2026 on Microsoft Azure Marketplace, the platform will offer an end-to-end view of all AI models and tools in use in an enterprise, whether built in-house or provided by third parties. Using it, enterprises will be able to apply internal policies and external regulations and frameworks to AI use cases.

“It’s giving visibility into your AI inventory,” Reggie Townsend, VP of SAS’ data governance and ethics practice, said at today’s event. “But it also answers the really basic question: How are we doing?”

Enterprises want “enough data at a glance” to consider tension points when they’re juggling factors like reputation, efficiency, and cost, he pointed out. They’re also viewing trust as a new business differentiator, even as a currency. 

Navigator started with a really simple idea, he noted: “What happens if we can make being responsible irresistible?” AI governance is one way to preserve human judgment amidst what he called “tech asymmetry.”

Technology unevenness has been a long-standing problem; While there’s strong technical capability, enterprises struggle to adapt to the pace of change at scale. “What folks need to do is try to translate some of these capabilities into a sustainable business advantage,” said Townsend.

As AI capabilities (and offerings) continue to expand, he urged users to gain “sufficient literacy,” approach AI with curiosity, and think critically about how evolving tools can apply to both business and personal life.

“In an emerging landscape like this, we’ve got to suspend certainty,” he said. “Certainty breeds rigidity, and rigidity suspends this idea of nuanced judgment, which we need right now.”

The next chapter of AI is about scaling that judgment, governing at speed, and turning trust into that competitive advantage, he emphasized.

Getting to the right enterprise data

Enterprise data can be fragmented across many different ecosystems (on-prem, in legacy infrastructure, or in private or public clouds), noted SAS industry market lead Alyssa Farrell. Beyond that, she said, “[enterprises] have low trust in the data itself, which is leading to low trust in decisions.” Further, performance constraints can hamper AI progress.

To address these issues, SAS today announced a targeted refresh of SAS Data Management, its cloud-native portfolio built on the Viya platform, adding or expanding its AI-ready data management, governance by design, agentic AI and copilots, and cloud-native analytic acceleration. It provides lineage, transparency, and control capabilities within workflows where data is accessed, prepared, and activated, Farrell explained.

“Agents and AI crave data more than ever before,” she said. “It’s really important that organizations get this right from the beginning, especially if they’re adding automation to that decision process.”

The re-architected platform grounds AI in trusted data, making raw data assets usable for AI. Notably, it brings analytics and AI to the data itself through SpeedyStore, the company’s cloud-native analytical data platform, negating the need to move volumes of data for processing, Farrell explained. Enterprises still retain digital sovereignty and can control workflows across their various data stores.

“We’re making sure our customers have everything they need to meet this moment [and] tools that access the data, manage the data and gain value from it,” Farrell noted. “They can really proceed at scale to operationalize AI with confidence.”

This article originally appeared on CIO.com.

HAX CMS 24.x - Stored Cross-Site Scripting (XSS)

Craft CMS 5.6.16 - RCE

GNU InetUtils 2.6 - Telnetd Remote Privilege Escalation

phpMyFAQ 4.0.16 - Improper Authorization

GeographicLib v2.5.1 - stack buffer overflow

OpenWrt 23.05 - Authenticated Remote Code Execution (RCE)