Enlarge (credit: IBM )

As the utility of AI systems has grown dramatically, so has their energy demand. Training new systems is extremely energy intensive, as it generally requires massive data sets and lots of processor time. Executing a trained system tends to be much less involved—smartphones can easily manage it in some cases. But, because you execute them so many times, that energy use also tends to add up.

Fortunately, there are lots of ideas on how to bring the latter energy use back down. IBM and Intel have experimented with processors designed to mimic the behavior of actual neurons. IBM has also tested executing neural network calculations in phase change memory to avoid making repeated trips to RAM.

Now, IBM is back with yet another approach, one that's a bit of "none of the above." The company's new NorthPole processor has taken some of the ideas behind all of these approaches and merged them with a very stripped-down approach to running calculations to create a highly power-efficient chip that can efficiently execute inference-based neural networks. For things like image classification or audio transcription, the chip can be up to 35 times more efficient than relying on a GPU.

Enlarge (credit: IBM )

Large Language Models, the AI tech behind things like Chat GPT, are just what their name implies : big. They often have billions of individual computational nodes and huge numbers of connections among them. All of that means lots of trips back and forth to memory and a whole lot of power use to make that happen. And the problem is likely to get worse.

One way to potentially avoid this is to mix memory and processing. Both IBM and Intel have made chips that equip individual neurons with all the memory they need to perform their functions. An alternative is to perform operations in memory , an approach that has been demonstrated with phase-change memory.

Now, IBM has followed up on its earlier demonstration by building a phase-change chip that's much closer to a functional AI processor. In a paper released on Wednesday by Nature, the company shows that its hardware can perform speech recognition with reasonable accuracy and a much lower energy footprint.

Enlarge / COBOL 73, as seen (inside Windows) in the IRS's Austin, Texas, offices in 2022. (credit: Washington Post / Getty Images)

There are hundreds of billions of lines of COBOL code running on production systems worldwide. That's not ideal for a language over 60 years old and whose primary architects are mostly retired or dead.

IBM, eager to keep those legacy functions on its Z mainframe systems , wants that code rewritten in Java. It tried getting humans to do it a few years back, but now it has another idea. Yes, you guessed it: It's putting AI on the job.

The IBM watsonx Code Assistant , slated to be available in Q4 this year, intends to keep humans in the mix, but with a push from generative AI in analyzing, refactoring, and testing the new object-oriented code. It's not an all-or-nothing process, either, as IBM claims that watsonx-generated code should be interoperable with COBOL and certain Z mainframe functions.

Enlarge / IBM's Eagle processor has reached Rev3, which means lower noise qubits. (credit: IBM )

Today's quantum processors are error-prone. While the probabilities are small—less than 1 percent in many cases—each operation we perform on each qubit, including basic things like reading its state, has a significant error rate. If we try an operation that needs a lot of qubits, or a lot of operations on a smaller number of qubits, then errors become inevitable.

Long term, the plan is to solve that using error-corrected qubits . But these will require multiple high-quality qubits for every bit of information, meaning we'll need thousands of qubits that are better than anything we can currently make. Given that we probably won't reach that point until the next decade at the earliest, it raises the question of whether quantum computers can do anything interesting in the meantime.

In a publication in today's Nature, IBM researchers make a strong case for the answer to that being yes. Using a technique termed "error mitigation," they managed to overcome the problems with today's qubits and produce an accurate result despite the noise in the system. And they did so in a way that clearly outperformed similar calculations on classical computers.

Enlarge / The IBM logo in front of an AI-generated background. (credit: IBM / Midjourney)

IBM Chief Executive Officer Arvind Krishna has revealed plans to halt hiring for about 7,800 positions that could be replaced by artificial intelligence systems in the near future, according to a Bloomberg news report published Monday.

Krishna said that hiring in back-office functions like human resources will be suspended or slowed, affecting roughly 26,000 non-customer-facing roles. "I could easily see 30 percent of that getting replaced by AI and automation over a five-year period," Bloomberg quoted Krisha as saying in an interview.

The announcement comes at a time when generative AI chatbots like ChatGPT have stirred anxiety about the future of human jobs. In March, Goldman Sachs released a report estimating that generative AI may " expose " 300 million jobs to automation, which means those roles might be reduced or replaced by AI systems.

Enlarge / A type ball from a 1961 IBM Selectric typewriter. (credit: Getty )

There are some feelings you just can't re-create. And to IBM Selectric loyalists, neither beam spring keyboards nor buckling spring designs nor a modern mechanical keyboard can replicate the distinct feel driven by that legendary type ball. In the '60s and '70s, the Selectric was an office staple, but the growth of PCs and daisy wheels forced the machine into retirement by 1986. That hasn't stopped people from buying, restoring, and selling Selectrics, though. The problem is, IBM stopped making the single printing element that makes those typewriters so special. You can find the type balls online, (including options claiming to be used and never used ) and at stores carrying old electronic components. But you'd save time and resources if you could make your own. It took years for someone to find a way to make the Selectric golf ball 3D-printable, but now someone claims they have.

A tinkerer named Sam Ettinger recently shared his Selectric type ball 3D-printing project on Hackaday and Github and shared the files on Printables , as reported by Hackaday . But beware: These finalized versions haven't been tested or printed by their creator. Earlier this month, Ettinger shared a video on Mastodon of the prior version in action, admitting that some letters weren't usable.

Ettinger said he typed this using a previous version of his 3D printable type ball featuring a Cherokee layout. (credit: settinger/Printables.com )

The new models are reportedly 0.2 mm shorter to address this and adjust the letter rotation, since it was "90 degrees off." Because of this, we can't verify how successful these models would be in real use.

Enlarge / Model F Labs' Classic Style F104 Model F keyboard starts at $420. (credit: Model F Keyboards )

IBM’s Model F keyboards are prized among keyboard enthusiasts. Introducing buckling spring switches over a capacitive printed circuit board (PCB) in the early 80s, they’re considered the grandfather of mechanical switches. Despite their prestige, Model F keyboards were no more by the following decade and, due to outdated technologies, have become very rare and can be tough to use with a modern computer. Targeting retro keyboard fans who don't want to deal with long searches, repairs, or mods, Model F Labs recreates IBM's Model F keyboards with modern OS support, and it recently introduced the iconic buckling spring switches in a classic full-sized keyboard, as well as some unique form factors.

Buckling springs

With the tactile buckling of the internal spring and the click of the flipper against the capacitive PCB, the keys in IBM's Model F keyboards inspired today's mechanical switches. Popular in banks, they replaced IBM's beam spring keyboards with a lower-cost design that was also less bulky. Early Model F keyboards had keycaps that were the same size, and keycaps were also removable for customization.

By 1985, IBM was making Model M keyboards , also popular among keyboard collectors today, with keys featuring a buckling spring over membrane and lower manufacturing costs.

Enlarge (credit: Getty Images )

Threat actors are exploiting a critical vulnerability in an IBM file-exchange application in hacks that install ransomware on servers, security researchers have warned.

The IBM Aspera Faspex is a centralized file-exchange application that large organizations use to transfer large files or large volumes of files at very high speeds. Rather than relying on TCP-based technologies such as FTP to move files, Aspera uses IBM’s proprietary FASP—short for Fast, Adaptive, and Secure Protocol—to better utilize available network bandwidth. The product also provides fine-grained management that makes it easy for users to send files to a list of recipients in distribution lists or shared inboxes or workgroups, giving transfers a workflow that’s similar to email.

In late January, IBM warned of a critical vulnerability in Aspera versions 4.4.2 Patch Level 1 and earlier and urged users to install an update to patch the flaw. Tracked as CVE-2022-47986, the vulnerability makes it possible for unauthenticated threat actors to remotely execute malicious code by sending specially crafted calls to an outdated programming interface. The ease of exploiting the vulnerability and the damage that could result earned CVE-2022-47986 a severity rating of 9.8 out of a possible 10.