Slack is turning its Slackbot helper into a more capable, personalized AI assistant that can perform actions such as drafting content and scheduling meetings.

Users have long been able to interact with Slackbot from channels and direct messages, where it can be asked to send reminders or notifications, or provide a preset response to keyword prompts such as what the Wi-Fi password is, among other tasks.

The revamped Slackbot, which is currently in pilot, will be accessible from a button at the top of the app. Once invoked, it will answer user queries based on information in conversations, files and other data stored in Slack, as well as Salesforce tools and connected third-party apps including Google Drive and Microsoft’s OneDrive, the company said.

As with other AI assistants on the market, the new Slackbot will perform a range of functions such as drafting content and summarizing reports. Slackbot will also be able to schedule a meeting by checking colleagues’ calendars for available times and will draft a meeting agenda and surface relevant documents ahead of the call.

The AI assistant runs on a combination of third-party large language models (Slack didn’t specify which) hosted by Amazon Web Services in a virtual private cloud.

The new Slackbot will initially only have access to data within a Slack workspace, but there are plans to connect to web data at a later date, a Slack spokesperson said. Other capabilities on the product roadmap include the ability to interact with and orchestrate other AI agents in Slack, as well as build AI agents for users without any coding. Slack recently announced developer tools to make it easier to connect with third-party AI assistants.

Among the other announcements at parent company Salesforce’s Dreamforce event this week is the general availability of channel agent. Accessible in a Slack channel, the agent is described as an “always on teammate” that can answer questions related to shared projects. This is included at no extra cost in Slack Business+ plans and above.

Updated enterprise search functionality will enable users to search for information across connected third-party apps such as Gmail, Dropbox, and Notion. This is available now on the Enterprise+ plan.

The updates are part of a wider drive to reshape the collaboration app as the interface for getting work done in Salesforce’s suite of business apps.

With this in mind, there are new integrations with four of Salesforce’s Agentforce agents. In Agentforce IT Service, for example, employees can get help with requests such as password resets from within Slack. The agent will also create an “incident channel” for more complex problems, automatically adding the relevant people and information. It’s available now on all Slack plans with a Salesforce Agentforce license, alongside Agentforce Sales, Agentforce HR Service, and Agentforce Tableau.

Source:: Computer World

By Deepti Pathak Over the years, One Piece has built not just an anime legacy but also a collection…
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An analyst recently offered an amusingly accurate observation about how Isaac Asimov’s three laws of robotics — from his classic 1950 science-fiction book “I, Robot” — would read today in a world of generative and agentic AI.

The first law was: “A robot may not injure a human being or, through inaction, allow a human being to come to harm.”

Valence Howden, an advisory fellow at Info-Tech Research Group, observed that if that book were updated for 2025, the first law might better be: “AI may not injure a hyperscaler’s profit margin.”

Let me elaborate. This is how I think the OpenAI crew might update the other two rules, which Asimov penned as “A robot must obey the orders given it by human beings except where such orders would conflict with the First Law” and “A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.”

Today’s version of the Second Law would be: “GenAI must obey the orders given it by human beings, except where its training data doesn’t have an answer and then it can make up anything it wants — and do so in an authoritative voice that will now be known as Botsplaining.”

And the third updated rule would be: “GenAI must protect its own existence as long as such protection does not hurt the Almighty Hyperscaler.”

I got to thinking about these laws after seeing a recent report about Deloitte Australia using genAI to write a report for a government agency —then having to partially refund its fee when authorities found multiple “nonexistent references and citations.”

Apparently, Deloitte published the information without anyone bothering to see whether it was, well, true. 

Irony alert: Deloitte is supposed to be telling enterprise IT executives the best way to verify and leverage genAI models, not demonstrate the worst-possible practices itself. (Then again, the latter approach is probably the more persuasive of the two.)

Maybe what we really need are three laws governing how enterprise IT should use genAI. 

Law One: “IT Directors may not injure their enterprise employers by not verifying genAI or agentic output before using it.”

Law Two: “A model must obey the orders given it by human being,s except when it doesn’t have sufficiently reliable data to do so. In that case, it is required to say ‘I don’t know.’ Making up stuff —without saying that you are making up stuff — is a major violation of this law.”

Law Three: “IT Directors must protect their own existence by not blindly using whatever genAI or agentic AI vomits onto their screen. Failure to do so will result in termination and — if the world has any justice left — lawsuist and being exiled to North Sentinel Island, where technology isn’t allowed.”

Let’s say the quiet part out loud: The kind of strict verification needed to get anything out of genAI that is usable and reliable is likely to gut the gorgeous ROI many CEOs are dreaming of. It’s a tool to help, not replace, workers. 

The simplest tactic is to treat AI information as a highly unreliable source. That doesn’t mean you ignore it. But it does mean you must treat the data accordingly. The ROI of these highly-flexible systems will still be there, even if the efficiency won’t be as high as execs want.

As a journalist, I have had extensive experience dealing with low-reliability sources. The technique is similar to dealing with an off-the-record source. 

People ask “Why would you ever accept information off-the-record? What good is it if you can’t publish it?” The answer relates to proper AI data procedures. If the off-the-record information prompts you to ask a question you wouldn’t have otherwise thought about or go somewhere you wouldn’t have otherwise gone, it’s potentially valuable.

A long time ago, I was a reporter for a daily newspaper in a large city and I was trying to find out what happened to city resources that had gone missing. A city hall source — very political and unreliable —  quietly told me: “You want to know what happened to (the items)? Go to this address. It’s a warehouse and look in the backroom.”

I asked, “What will I find there?” He replied “Your answer.” I didn’t have a lot of confidence in the mission, but the address was close by so I went. Sure enough, the backroom gave me the answer. (The details of what was missing is anticlimactic, but there were some 60,000 missing street signs.)

That’s how to deal with what genAI tools produce. Don’t assume it’s correct, but feel free to ask questions — and make other inquiries — based on that information. It can be helpful, if you do the legwork.

It’s important to remember that for every right answer genAI delivers, there will be many wrong answers. (The hyperscalers often seem to forget to mention that.) And sadly, “wrong answers” are not limited to hallucinations.

Hallucinations often occur when a large language model (LLM) doesn’t know the correct answer because it has not been trained, or fine-tuned, with that information.

But it also often has low reliability data. As I have noted before, “In healthcare, for example, it might be the difference between using the New England Journal of Medicine or Lancet versus scraping the personal website of a chiropractor in Milwaukee.”

And even if the data is reliable, it might be out of date. Or it might be in the wrong language and the translation is off. Or it might refer to the wrong geography. (A correct answer in the US might not be the correct answer in Japan or France.)

And even if the germane data exists and is highly reliable, the model can still misinterpret it. For that matter, it might also misinterpret your user’s query. 

When thinking about genAI reliability, it’s important to split AI functions into two categories — informational, such as when asking a question or seeking a recommendation and Action, such as when you ask a system to code or to create a series of spreadsheets or to make a short movie.

Action requests require more due diligence, not less. Does that kill the ROI? It might. But if it does, maybe there was never any meaningful ROI in the first place.

Source:: Computer World

By Deepti Pathak Krafton has announced a power-packed partnership between BGMI and Bollywood superstar Tiger Shroff. From October 8,…
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Intel unveiled its Core Ultra series 3 processors on Thursday, the first client chips built on its 18A process node and manufactured in Arizona, as enterprises gear up for a wave of PC refreshes driven by Microsoft’s October 2025 end-of-support deadline for Windows 10.

The Panther Lake platform delivers up to 180 platform TOPS for AI workloads through a balanced design that distributes processing across CPU, GPU, and neural processing units. Systems are expected to reach broad availability in January 2026, Intel said in a statement.

But while Intel is pitching AI acceleration as a key differentiator, analysts say most enterprise buyers remain unconvinced that on-device AI processing justifies the investment — even as survey data suggests they’re buying AI-capable hardware anyway.

Made in America, bought for other reasons

Intel emphasized its domestic manufacturing capability during the announcement. CEO Lip-Bu Tan said the company is “entering an exciting new era of computing” enabled by semiconductor advances, highlighting US production at Fab 52 in Chandler, Arizona, as central to Intel’s strategy.

The 18A node incorporates RibbonFET transistor architecture and PowerVia backside power delivery, with Intel claiming approximately 15% better performance per watt and 30% improved chip density compared to its Intel 3 process.

However, from an enterprise procurement perspective, manufacturing location carries limited weight for most buyers, according to Manish Rawat, semiconductor analyst at TechInsights.

“Intel’s ‘18A’ and ‘Made in America’ positioning primarily resonates with government, defense, and regulated industries where supply chain assurance and data sovereignty are critical,” Rawat said. “For the broader enterprise market, purchasing decisions remain driven more by performance-per-watt, TCO, platform stability, and manageability than by fab location.”

Maciek Gornicki, senior research manager for IDC’s Client Devices Group in Asia/Pacific, agreed. “The product’s ability to support business operations is the much bigger factor,” he said, though noting the 18A node “looks to deliver improvements in performance and efficiency.”

While US chip fabrication could benefit government procurement under Buy American provisions, it’s unlikely to affect tariffs on finished laptops, which are classified based on final assembly location rather than component sourcing.

180 TOPS in search of a killer app

Panther Lake features up to 16 cores and a new Intel Arc GPU with up to 12 Xe cores, with Intel claiming more than 50% performance improvements over previous generations. The company also previewed Xeon 6+ (codenamed Clearwater Forest), its first 18A-based server processor scheduled for first-half 2026 launch with up to 288 efficiency cores.

However, enterprises continue to view AI acceleration on client devices as a niche requirement rather than a universal need, according to Rawat.

“While Intel’s 180 TOPS figure is impressive on paper, most organizations still rely on cloud-based AI for scalability, central model management, and consistent performance,” he said. For sentiment to shift, enterprises need proven productivity gains from on-device inference, software ecosystems that fully exploit local AI hardware, and quantifiable cost savings compared to cloud AI usage fees. “Without that clear ROI, IT departments are unlikely to pay a premium for AI-capable endpoints.”

Gornicki echoed this, noting AI PC use cases remain works in progress. “Macroeconomic uncertainty also means that some organizations feel compelled to buy lower-priced systems, sometimes without NPUs,” he said.

Intel has been enabling developers to leverage local AI processing for advantages in privacy, personalization, and potential cost savings, Gornicki noted. “But it will still take a few years before we start to see bigger use cases.”

Futureproofing trumps immediate need

According to Gornicki, PC refresh activity stems from three factors: replacement of pandemic-era devices, Windows 11 migration, and AI adoption considerations.

“Key challenge around the AI PC adoption is the lack of game-changing killer applications which would make PC hardware refresh absolutely necessary,” Gornicki said.

Yet according to IDC survey data cited by Gornicki, 70% of organizations perceive AI capabilities as a top, critical, or very important factor for next-wave deployments, with 39% planning to upgrade the majority of their devices within 12 months to benefit from AI PC capabilities. Gornicki said IDC forecasts AI PCs will account for just over 50% of commercial shipments globally by 2026.

The apparent contradiction — high stated interest without clear business cases — suggests enterprises are hedging their bets, purchasing AI-capable hardware for futureproofing rather than immediate requirements. IDC projects overall PC shipments will grow 4.3% in 2025, driven primarily by the Windows refresh requirement.

Intel faces intensified competition

Intel’s launch comes as AMD has gained market share, and Qualcomm’s Snapdragon X series targets Windows on Arm deployments.

“Panther Lake signals Intel’s attempt to reclaim leadership after ceding ground to AMD in multi-core efficiency and to Arm-based systems in battery life and AI optimization,” Rawat said. “If Intel delivers on both 18A efficiency gains and integrated AI acceleration without thermal compromises, it could narrow the gap and stabilize market share in 2025-2026 refresh cycles.”

However, many enterprises have diversified vendors to avoid single-source dependency, Rawat noted, and AMD’s competitive pricing remains appealing. Arm’s penetration into enterprise laptops with growing Windows-on-Arm optimization adds additional pressure.

“Panther Lake helps Intel re-enter the leadership narrative but does not yet guarantee a decisive shift in enterprise buying behavior until real-world benchmarks validate its advantages,” Rawat said.

Gornicki cited IDC survey data that shows more than half of businesses are open to considering AMD or Qualcomm-based devices. “Panther Lake will undoubtedly ensure that Intel remains relevant and very often first choice among enterprises that seek to remain on Intel Architecture,” he said, though characterizing the launch as an expected development rather than a game-changer.

More Intel news:

AMD could be Intel’s next foundry customer

Who wins/loses with the Intel-Nvidia union?

Intel will design CPUs with Nvidia NVLink in return for $5 billion investment

Source:: Computer World

If you know your way around platform security, you don’t need to sell your discoveries to dodgy surveillance-as-a-service firms — Apple will make you a millionaire. During his speech at Offensive Security event Hexacon 2025, Ivan Krstić, Apple’s head of Security Engineering and Architecture (SEAR), announced a big increase in the top award available under the Apple Security Bounty scheme.

Make millions, do the right thing

The bounty now maxes out at $2 million for exploit chains that can achieve similar goals as sophisticated mercenary spyware attacks. That bonus also stacks with other security bounties Apple provides, meaning researchers can make up to $5 million when they identify a new series of exploits.

From November, Apple is also doubling or significantly increasing rewards in many other categories to encourage more intensive research. These new awards include $100,000 for a complete Gatekeeper bypass and $1 million for broad unauthorized iCloud access — though Apple does say no successful exploit has been demonstrated to date in either of these categories.

Apple has also introduced bonuses for WebKit sandbox escapes and wireless proximity exploits.

Why does Apple pay so much?

Apple began paying for information of this kind relatively recently in 2019. It was about then that the nature of these attacks began to change as governments and government-adjacent ‘security’ firms began to make serious attacks against the company’s customers. 

Later on, in 2022, the company announced Lockdown Mode, its high-security system that helps deliver even stronger protection for potentially vulnerable targets. It also released $10 million to help support organizations that investigate, expose, and prevent highly targeted cyberattacks. These efforts continue.

They must. We’ve seen numerous instances of such attacks since then, particularly but not exclusively on the part of mercenary spyware firms. Apple, in turn, continues to ramp up security protection across all its products and services. 

While attempting to secure its platforms and its customers, Apple must also grapple with authoritarian, irresponsible governments, which make decisions that inevitably weaken security. The UK’s attempt to carve a back door into encrypted iCloud data is just one example. It is obvious that Apple will need to invest even more than it already does in security in order to protect these now weakened flanks. 

You, them, and MIE

Krstić also discussed Memory Integrity Enforcement (MIE), a new security protection Apple announced alongside the iPhone 17. Five years in development, this defense aims to protect against the most frequently exploited kinds of iOS bugs, memory safety vulnerabilities, which are often used in the sophisticated surveillance-as-a-service attacks so popular among some of the world’s most repressive regimes. 

“The only system-level iOS attacks we observe in the wild come from mercenary spyware — extremely sophisticated exploit chains, historically associated with state actors, that cost millions of dollars to develop and are used against a very small number of targeted individuals,” the company said.

These are the attacks wielded against activists, journalists, and politicians. (Apple is donating 1,000 iPhone 17s to rights groups that work with people at risk of targeted attacks, according to Wired.)

Combined protections such as MIE, Lockdown Mode, and the other security shields that exist on Apple’s platforms make these sophisticated attacks much more expensive to develop and use, but Apple knows the security struggle continues, which is why it has increased the security bounties it provides.

A ‘moral obligation’

Speaking to Wired, Kristić explained why Apple puts so many resources into protecting these high-value target groups: “We feel a great moral obligation to defend those users. Despite the fact that the vast majority of our users will never be targeted by anything like this, this work that we did will end up increasing protection for everyone.”

He’s right, of course, because the inconvenient truth of living on a digitally connected planet is that no one is safe until all are safe. That means any attempt to weaken security for one group of people will inevitably reduce the security of all groups of people.

Follow me on social media! Join me on BlueSky,  LinkedIn, and Mastodon.

Source:: Computer World

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The UK government has announced plans to appoint a “digital markets champion” as part of its drive to modernize the way financial transactions are conducted by adopting blockchain-based shared ledgers.

News of the new role was announced by Economic Secretary to the Treasury Lucy Rigby, in a speech on Wednesday at the Digital Assets Week conference in London.

It’s not yet clear who might be in line for the job, but the individual will need to be an industry figure with enough knowledge and connections to get competing agencies – the Bank of England, the UK Treasury, and the Financial Conduct Authority (FCA) – to agree to a common framework.

The government is also setting up a new group, the Dematerialisation Market Action Taskforce (DEMAT), to co-ordinate the UK’s move away from paper-based share certificates. 

Tech suppliers are also being invited to bid to take part in the government’s Digital Gilt Instrument (DIGIT), a platform to issue sovereign debt, Rigby is reported to have said.

The range of initiatives underlines the complexity of migrating the financial system from the manual, paper-based systems that have been in use for centuries to ones that are fully digital.

Token effort

In July, the government set out the arguments for change in its Wholesale Financial Markets Digital Strategy policy paper, saying today’s financial processes are slow, costly, and rely on manual systems, which together stifle financial innovation.

Adopting blockchain Distributed Ledger Technology (DLT) would, the paper argued, allow financial assets to exist as tokens on shared ledgers, overhauling markets by lowering costs, dramatically speeding up transactions, and increasing transparency.

“The ‘tokenisation’ of assets could deliver a step change in market efficiency, for instance by enabling real-time data sharing which could improve transparency and lower operational costs,” the paper said.

“More broadly, it could enable a fundamental reimagining of the way financial markets operate, creating infrastructures that support both existing and new forms of asset issuance, transfer, and ownership.”

Despite this, the UK is at risk of falling behind its international peers in ways that will soon hinder London’s preeminence as a financial hub. The EU already has the EU DLT Pilot Regime and Markets in Crypto-Assets Regulation (MiCA), the US has the Genius Act for stablecoins, and Singapore has Project Guardian.

Additionally, Swift, the global financial messaging network, recently announced that it would introduce blockchain-based ledger as part of its platform, an initiative it has been testing for several years.

The organization is developing a prototype shared digital ledger to accelerate cross-border payments in conjunction with 30 global financial institutions and blockchain company Consensys.

This will eventually extend the Swift platform to validate transactions and enforce rules governing smart contracts, the organization said.

“You may think, ‘Wow, aren’t those opposites? Swift and blockchain. Traditional finance and decentralized finance. Can they really go together?’ In the regulated system of the future, we believe they can. Banks are ready for it. And they’re asking us to play a bigger role,” said Swift CEO Javier Perez-Tasso at the Sibos 2025 conference.

In the UK, progress towards a regulatory environment remains a work in progress, with a lot of detail still unclear. For now, the Treasury and the FCA are still at the stage of producing policy papers.

According to Julia Demidova of FinTech company FIS Global, the first job of the new digital markets champion will be to work with the Bank of England, the FCA, and the Treasury. 

“The champion will try to achieve some kind of consensus between the three parties. We need a champion in this space to reduce some of the frictions that exist,” Demidova told Computerworld. “We haven’t been moving fast enough in comparison to other markets such as the EU, which has a consensus on what MiCA is.”

The UK needs to develop a clear set of priorities as soon as possible, especially over how it plans to support asset classes such as stablecoins, she said. Right now, there is a lack of clarity over whether these can be used for payments.

“The champion will have to establish what’s missing today from the existing regulatory frameworks.” said Demidova.

The UK government has recognized this need. In Demidova’s view, this suggests the digital champion will have the political backing to unblock the regulatory process.

Lurking in the background to all this is the security of technologies that are still unproven under real-world conditions. “These are new, emerging technologies, and this brings some potential cyber security issues that we may not know about. This is a new surface for attacks that might emerge in this ecosystem,” cautioned Demidova.

It’s a debate that will interest IT management, an analyst noted. “The challenge for CIOs is integration. Legacy ERPs weren’t built for immutable, token-based workflows,” commented Dan Silverman, co-CEO at data intelligence company, Balcony.

“Tokenization isn’t just financial, it’s foundational for secure, verifiable data exchange across public and private systems,” he added. The risk is that the effect of uncertainty on businesses is ignored in favor of institutional interests, not least because countries are adopting these technologies at different rates.

Source:: Computer World

The Discord user data breach offers yet another argument against the UK government’s authoritarian plans for Digital ID. A sensible government would consider the implications before forcing people to risk information with a stunt like this.

So, what happened? 

The online speculation is that millions of government ID data items might have been stolen in an attack against an identity verification service used by Discord. Discord says it has “identified approximately 70,000 users that may have had government-ID photos exposed, which our vendor used to review age-related appeals.” 

It also said it is communicating with users affected by the hack and is working with law enforcement to investigate the matter.

What happened at Discord?

“Recently, we discovered an incident where an unauthorized party compromised one of Discord’s third-party customer service providers. The unauthorized party then gained access to information from a limited number of users who had contacted Discord through our Customer Support and/or Trust & Safety teams,” the company said in a statement.

The leaked information included:

Name, Discord username, email and other contact details provided to Discord customer support.

Payment type, last four digits of credit cards, and purchase history if associated with an account.

IP addresses.

Customer service agent messages.

Limited corporate data (training materials, internal presentations).

A small number of government‑ID images (e.g., driver’s licenses or passports) from users who had appealed an age determination.

The data did not include passwords, authentication data, full credit card numbers, CCV codes or messages shared on Discord, beyond those with customer support.

This is completely predictable

While I think the phrase “a small number” might be doing a lot of work here, the attack is completely predictable. It seems inevitable that once governments — such as the current UK administration — force users to share high-level security data simply to use social media, the unregulated services that verify those ID documents will become attractive targets for attack.

This is precisely what happened at Discord. That company turned to a third party to handle inquiries of this kind, that third party was hacked, and valuable data was stolen. This isn’t even the first such attack. A year ago, an attack against US ID verification service AU10TIX exposed names, dates of birth, nationality, identification numbers, the type of documents uploaded (such as a drivers’ license) and images of those documents. 

It is completely anti-intuitive to expect Discord will be the only ID verification partner facing attacks, and it is futile to believe for one iota of a second that this will be the only such partner to succumb to those attacks. That the ID provision companies are subject to only light regulation makes this a massive threat to digital security — particularly given potential links between them and foreign intelligence agencies.

Surveillance and security, UK style

This is a big challenge for UK users, so recently forced to share such information with social media services in response to the UK’s so-called Online Safety Act (a piece of legislation that leaves us all less safe then before). Anyone in the UK who shared this information with Discord’s ID verification service in response to that Act has been left exposed by the government’s ineptitude. It’s not as if experts on online privacy and security did not warn of the potential consequences, but the government chose not to listen, preferring to maintain its addiction to state surveillance. 

Every UK subject who finds their personal information compromised as a result of sharing ID documents — just to keep visiting their favorite online gaming community on Discord — has only one entity to blame, and it’s not Discord. It’s the UK government.

The big picture

This absolutely won’t be the last big break-in for this kind of user data. Quite apart from financial fraud, criminals also know how to use legitimate passport data to create fake IDs. And the net result of hacks like this will be deep security exposure for UK citizens and a whole flotilla of fake documentation to be shared across criminal groups, hostile nation states, and refugees seeking safety. 

Indeed, far from making the online or physical world any safer, UK ineptitude has effectively created a big dollop of insecurity we haven’t even felt the impact of yet. As more such services are hacked, more damage will be done. 

Prepare for worse

With the UK committed to forcing Digital ID on an unwilling nation, there is a high probability it will become a target. That would matter less if online security could be guaranteed, but it can’t. And these days, every business doing digital business has adopted a “when” not “if” approach to security.

In other words, they know they will be hacked or attacked one day, and will have plans in place for what to do when it happens. The UK ID experiment might approach security in a similar way, but it is certain it will be attacked, some attacks will succeed, and data stolen in those attacks will be abused. 

Discord’s misfortune is a warning of what’s to come. It is certainly an indication that before people are forced to use third-party verification services, a set of regulatory standards and a legal apparatus for generous compensation if a user is impacted should be in place.

At present, this does not exist, which means these systems leave us more exposed to fraud and other online harms than we were before.

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Source:: Computer World

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In a boost to the profile of quantum computing, the Nobel Prize Committee has awarded this year’s Physics prize to three pioneers in the field of quantum research: John Clarke, Michel H. Devoret and John M. Martinis, “for the discovery of macroscopic quantum mechanical tunneling and energy quantization in an electric circuit”.

This was a significant development. It had long been recognized that quantum mechanics would allow a particle to move straight through a barrier, using this tunneling process. However, once large numbers of particles were sent through the barrier, it had not been possible to see any quantum mechanical effects. The prizewinners’ experiments changed all that: it showed that such properties could be observed on a larger scale. However, “macroscopic” in quantum terms still means a system that is small enough to be hand held.

In a statement, the Nobel committee said “The transistors in computer microchips are one example of the established quantum technology that surrounds us. This year’s Nobel Prize in Physics has provided opportunities for developing the next generation of quantum technology, including quantum cryptography, quantum computers, and quantum sensors.”

While this work was ground-breaking at the time, since it was originally carried out in 1984 and 1985 at the University of California at Berkeley, and has only just been recognized by the Nobel Prize Committee, it does not reflect the latest state-of-the-art research in the field of quantum mechanics. However, as the committee pointed out, its findings have had important implications within the computing sector.

It’s the second year that the Nobel Prize Committee has had developments in information technology in its sights. This award follows the 2024 Prize in Physics awarded to Geoffrey Hinton and John Hopfield for their work in neural networks and machine learning.

Quantum impact in computing today

While this year’s prize may be rewarding research work that was carried out 40 years ago, it’s a reminder of the impact that quantum is starting to have on the world of computing. The award has certainly tapped into the zeitgeist: last December, the United Nations decreed that 2025 would be the year of quantum science. And there are plenty of examples of companies looking to bring the technology to market, even if widespread use of quantum is some way in the future.

For example, earlier this year we saw IBM team up with AMD to explore possibilities for quantum research, and Microsoft has also been active in developing scalable quantum technology. And just last week, HSBC used IBM processors to show that quantum has a part to play in automated trading, with the bank expected to develop the concept further after a successful trial.

Quantum, along with AI, is also an important part of the UK’s Digital Plan.

However, some industry experts have commented on the timeline for practical quantum computing, pointing out that, despite the advances, we are still a long way from the technology becoming a reality for most organizations.

In addition, there are concerns that further development of the technology will have some deleterious effects. IT security specialists have warned that quantum computing could provide cyber criminals with a new weapon.

Source:: Computer World

High-end computer mice can be used to eavesdrop on the voice conversations of nearby PC users, researchers from the University of California, Irvine, have shown in a new proof-of-concept demonstration.

Given the catchy name ‘Mic-E-Mouse’ (Microphone-Emulating Mouse), the ingenious technique outlined in Invisible Ears at Your Fingertips: Acoustic Eavesdropping via Mouse Sensors is based on the discovery that some optical mice pick up incredibly small sound vibrations reaching them through the desk surfaces on which they are being used.

These vibrations could then be captured by different types of software on PC, Mac or Linux computers, including non-privileged ‘user space’ programs such as web browsers or games engines or, failing that, privileged components at OS kernel level.

Source:: Computer World

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By Deepti Pathak Vivo X300 Pro is getting hype even before it’s about to be released. Various leaks have…
The post vivo X300 Launching This Month: 5 Things We Know So Far appeared first on Fossbytes.

Source:: Fossbytes

By Deepti Pathak OpenAI recently released a new video creation app called Sora 2. The app essentially functions as…
The post How To Get Sora 2 Invite Code Right Now? appeared first on Fossbytes.

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IT services are changing. Their future will be defined by extensibility via APIs and artificial intelligence. It appears we’re moving toward a post-app digital economy, where personalization takes precedence over off-the shelf solutions. 

That seemed to be the message from Jamf at its 16th annual Jamf Nation User Conference (JNUC) in Denver, CO, where the company unveiled a new API ecosystem, AI capabilities, and automated software updates powered by Apple’s Declarative Device Management (DDM).

“This year marks a major evolution in how customers engage with Jamf,” Jamf CEO John Strosahl said in a statement. “These capabilities make it easier than ever for organizations to fully realize the potential of the Apple ecosystem — with features that matter, integrate seamlessly, and work the way customers need them to.”

When device management gets smarter

The company says these APIs should help its platform become a dynamic and flexible foundation for innovation. In essence, it means developers, admins, and security teams can use Jamf’s APIs to streamline automation, ease integration, and help manage/secure Apple devices at scale.

The idea is that organizations using the Platform APIs can build management tools personalized for the needs of their specific environment. This could be of use to IT and security teams building custom workflows as well as helping technology partners seeking to extend what Jamf can do with their own products and services. MacPaw is at JNUC to show how CleanMyMac Business already benefits from Jamf integration.

There seems to be an emerging rule that nothing in tech can be said unless there’s some mention of artificial intelligence, and Jamf is keeping to that exhortation. The company gave security protection an AI boost with Security Skill in Jamf Protect. It’s an AI assistant designed to help security teams by analyzing telemetry and events logs to provide plain-language incident guidance they can use, hopefully accelerating response. 

An extra security AI agent

“By simplifying complex frameworks such as MITRE ATT&CK and CVE references into actionable insights, the new capability enables security teams to cut through alert fatigue and focus on what matters most,” said Jamf.

The company shared initial reactions to the new solution at JNUC, stressing that the tool was delivering real solutions to real problems. In one example, Jamf demonstrated an AI analysis of a Time Stamping security alert. The AI considered the alert, analyzed it, and provided remediation in just seconds for IT. The feature is expected to arrive later this year. Jamf also confirmed it is using AI across the company to help build code and run operations — even turning to autonomous code agents.

“Every efficiency we bring with AI translates into productivity enhancements for you,” a Jamf executive told the audience of Apple admins. “This is enterprise AI done right.”

API, AI, and…DDM 

Declarative Device Management was always described as being the future of device management on Apple; now, it’s become part of the present. Jamf introduced Blueprints at JNUC 2024 and has now extended this support with new DDM-based workflows, including automated software update settings declarations; they basically let a managed device handle its own system updates based on policies defined by IT. This automates one of the pain points of managing Apple fleets and reduces the need for oversight through better automation. 

Digital everything

Reading between the lines of Jamf’s news from its show, it seems the company hopes to provide customers with the kind of extensibility they seek alongside the rock-solid platform security Jamf helps provide. 

The question is, as device management services become API-driven, at what point might some IT admins migrate to open-source alternatives, which also provide opportunities to build a new approach? 

Jamf, of course, can point to the market-tested resilience of its own platforms in contrast to other approaches. But there’s little doubt this will be part of the discussion in this part of the Apple industry over the coming months – especially since open source MDM provider Fleet cast some shade over the Jamf event. The latter has now become the biggest single sponsor of the largest IT group in the industry, the Mac Admins Foundation. Of course, the growing competition in the space reflects the extent to which the Apple-in-the-enterprise world is growing.

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Source:: Computer World

Imagine a city hub where a multitude of AI agents can gather, interact, and converse. Office workers are more like sentries — seeing and interacting with the information generated by agents at the hub.

Buses move information from various “neighborhoods” to the city hub, where workers can build AI agents and skills, and use productivity applications that leverage the growing knowledge base. Those sources could be from Slack, Microsoft or even legacy systems.

That’s how Dheeraj Pandey, co-founder of DevRev, described “Computer,” which his company unveiled last month. (Pandey previously co-founded and served as CEO of Nutanix.)

“We are the bus,” Pandey said in referencing the enterprise integration approach. The “bus” term is also a reference to Tibco’s service bus, which did bidirectional data transfers between data sources.

DevRev’s Computer aims to bring connective tissue to disparate systems, effectively unlocking previously unused data — generally referred to as unstructured data — and delivering new context to the information used by companies to make key decisions.

“What you build on top of all of this is basically agents and skills. We also build apps,” Pandey said. 

Those insights are made accessible to office workers through a conversational user interface. The DevRev stack adds more context through its own reasoning, indexing, and data processing.

“Computer…unifies both structured and unstructured data with extreme depth of organization to eliminate these silos and give AI agents full context,” Pandey said.

Box, Microsoft and Google in the last year have released AI features that can conduct deep research and add context to unstructured data. Those companies are plugging AI features into their legacy strengths in storage and productivity. 

DevRev’s Computer functionality goes beyond simple systems integration, Pandey said. “We like to take the agent approach before we go to the apps. We are the only AI company that can replace apps as well,” Pandey said.

Pandey described Computer as a kind of Switzerland where all AI offerings are treated equally. There is no lock-in to specific platforms or data sources, where only a limited amount of data is shared between systems. It provides a platform where workers can draw input from all data.

DevRev’s Computer creates its own knowledge graph from the information transported by the bus to the city hub. The goal is to turn “enterprise data into like a living network that maps complex relationships between teams, customers and products,” Pandey said.

A technology called AirSync is a key component powering the technology. It is a bidirectional synchronization technology that moves information back and forth from various systems to feed the AI-native knowledge graph.

Workers build agents that access the hub through a search engine, a SQL engine, and an MCP (Model Context Protocol) gateway. Orchestrators continuously extract and load data from external systems, while agents apply reasoning to automate workflows and present information to users through a conversational interface.

“The SQL engine runs on users’ devices at the edge, enabling fast queries without relying on cloud infrastructure. That’s a design choice that makes the system more affordable and responsive,” Pandey said.

Workers need to invoke workflows via large language models (LLMs) through an engine that’s being published through MCP.  “Basically you’re taking all your automations and annotating them, labeling them, and really publishing it through the MCP protocol,” Pandey said.

For customers, it takes just “seven lines of code” to deploy Computer into a web portal or application.

“Our customer’s employees will use this through a desktop app. It will auto-upgrade whenever it has to. It basically starts with a search bar. And the search bar eventually becomes a ChatGPT-like interface.”

APIs connect to existing systems, and DevRev’s marketplace already has many connectors built in. “Once they have deployed the marketplace connectors, everything just flows in,” Pandey explained.

The product name “Computer” was inspired by Peter Drucker’s 1967 article “The Manager and the Moron.”  (In the article, the moron caricature was a computer.)

“In 1967, he was conceiving what the computer could do,” Pandey said. “And we said, look, we can look at this as a more intelligent computer. It’s a more intelligent moron, but it’s not here to take your job.” 

Source:: Computer World