The head of Indian IT company Tata Consultancy Services has said AI will result in "minimal" need for call centres in as soon as a year, with AI's rapid advances set to upend a vast industry across Asia and beyond. From a report: K Krithivasan, TCS chief executive, told the Financial Times that while "we have not seen any job reduction" so far, wider adoption of generative AI among multinational clients would overhaul the kind of customer help centres that have created mass employment in countries such as India and the Philippines. "In an ideal phase, if you ask me, there should be very minimal incoming call centres having incoming calls at all," he said. "We are in a situation where the technology should be able to predict a call coming and then proactively address the customer's pain point." He said chatbots would soon be able to analyse a customer's transaction history and do much of the work done by call centre agents. "That's where we are going...I don't think we are there today -- maybe a year or so down the line," he said.

Hartley Charlton reports via MacRumors: Apple is said to be developing its own AI server processor using TSMC's 3nm process, targeting mass production by the second half of 2025. According to a post by the Weibo user known as "Phone Chip Expert," Apple has ambitious plans to design its own artificial intelligence server processor. The user, who claims to have 25 years of experience in the integrated circuit industry, including work on Intel's Pentium processors, suggests this processor will be manufactured using TSMC's 3nm node.

Apple's purported move toward developing a specialist AI server processor is reflective of the company's ongoing strategy to vertically integrate its supply chain. By designing its own server chips, Apple can tailor hardware specifically to its software needs, potentially leading to more powerful and efficient technologies. Apple could use its own AI processors to enhance the performance of its data centers and future AI tools that rely on the cloud. While Apple is rumored to be prioritizing on-device processing for many of its upcoming AI tools, it is inevitable that some operations will have to occur in the cloud. By the time the custom processor could be integrated into operational servers in late 2025, Apple's new AI strategy should be well underway.

Axon on Tuesday announced a new tool called Draft One that uses artificial intelligence built on OpenAI's GPT-4 Turbo model to transcribe audio from body cameras and automatically turn it into a police report. Axon CEO Rick Smith told Forbes that police officers will then be able to review the document to ensure accuracy. From the report: Axon claims one early tester of the tool, Fort Collins Colorado Police Department, has seen an 82% decrease in time spent writing reports. "If an officer spends half their day reporting, and we can cut that in half, we have an opportunity to potentially free up 25% of an officer's time to be back out policing," Smith said. These reports, though, are often used as evidence in criminal trials, and critics are concerned that relying on AI could put people at risk by depending on language models that are known to "hallucinate," or make things up, as well as display racial bias, either blatantly or unconsciously.

"It's kind of a nightmare," said Dave Maass, surveillance technologies investigations director at the Electronic Frontier Foundation. "Police, who aren't specialists in AI, and aren't going to be specialists in recognizing the problems with AI, are going to use these systems to generate language that could affect millions of people in their involvement with the criminal justice system. What could go wrong?" Smith acknowledged there are dangers. "When people talk about bias in AI, it really is: Is this going to exacerbate racism by taking training data that's going to treat people differently?" he told Forbes. "That was the main risk."

Smith said Axon is recommending police don't use the AI to write reports for incidents as serious as a police shooting, where vital information could be missed. "An officer-involved shooting is likely a scenario where it would not be used, and I'd probably advise people against it, just because there's so much complexity, the stakes are so high." He said some early customers are only using Draft One for misdemeanors, though others are writing up "more significant incidents," including use-of-force cases. Axon, however, won't have control over how individual police departments use the tools.

Lenovo's latest ThinkPad P1 Gen 7 laptop is set to be the first to use the new LPCAMM2 memory form factor, the successor to SODIMM sticks. From a report: While Lenovo has largely focused on the AI performance of its new laptop, which is equipped with an Intel Core Ultra CPU and Nvidia RTX 3000 Ada GPU, the company also noted that its device was the first in the world to use the LPCAMM2 memory standard. LPCAMM2 uses 64 percent less space than SODIMM and 61 percent less active power, according to Lenovo. This is thanks to it being based on LPDDR5X memory instead of regular DDR5.

Designed specifically for laptops, the LPCAMM2 standard actually has its origins in tech developed by Dell. Simply termed CAMM (Compression Attached Memory Module), it first debuted as a proprietary type of memory in Dell's Precision 7670 in 2022. However, in 2023 the PC giant donated its intellectual property to JEDEC, the organization that standardizes memory technologies. CAMM became LPCAMM2 (Low-Power Compression Attached Memory Module) in September 2023 when JEDEC finally confirmed its specifications. Samsung promptly announced plans to produce LPCAMM2 sticks, and claimed they would have 50 percent more performance and 70 percent more efficiency than their SODIMM-based predecessors. Plus, LPCAMM2 can offer dual-channel memory without requiring a second module.

Adobe researchers have developed a new generative AI model called VideoGigaGAN that can upscale blurry videos at up to eight times their original resolution. From a report: Introduced in a paper published on April 18th, Adobe claims VideoGigaGAN is superior to other Video Super Resolution (VSR) methods as it can provide more fine-grained details without introducing any "AI weirdness" to the footage. In a nutshell, Generative Adversarial Networks (GANs) are effective for upscaling still images to a higher resolution, but struggle to do the same for video without introducing flickering and other unwanted artifacts. Other upscaling methods can avoid this, but the results aren't as sharp or detailed. VideoGigaGAN aims to provide the best of both worlds -- the higher image/video quality of GAN models, with fewer flickering or distortion issues across output frames. The company has provided several examples here that show its work in full resolution.

Just as Google, Samsung and Microsoft continue to push their efforts with generative AI on PCs and mobile devices, Apple is moving to join the party with OpenELM, a new family of open source large language models (LLMs) that can run entirely on a single device rather than having to connect to cloud servers. From a report: Released a few hours ago on AI code community Hugging Face, OpenELM consists of small models designed to perform efficiently at text generation tasks. There are eight OpenELM models in total -- four pre-trained and four instruction-tuned -- covering different parameter sizes between 270 million and 3 billion parameters (referring to the connections between artificial neurons in an LLM, and more parameters typically denote greater performance and more capabilities, though not always).

[...] Apple is offering the weights of its OpenELM models under what it deems a "sample code license," along with different checkpoints from training, stats on how the models perform as well as instructions for pre-training, evaluation, instruction tuning and parameter-efficient fine tuning. The sample code license does not prohibit commercial usage or modification, only mandating that "if you redistribute the Apple Software in its entirety and without modifications, you must retain this notice and the following text and disclaimers in all such redistributions of the Apple Software." The company further notes that the models "are made available without any safety guarantees. Consequently, there exists the possibility of these models producing outputs that are inaccurate, harmful, biased, or objectionable in response to user prompts."

Nvidia, in a blog post: To help customers make more efficient use of their AI computing resources, NVIDIA today announced it has entered into a definitive agreement to acquire Run:ai, a Kubernetes-based workload management and orchestration software provider. Customer AI deployments are becoming increasingly complex, with workloads distributed across cloud, edge and on-premises data center infrastructure.

Managing and orchestrating generative AI, recommender systems, search engines and other workloads requires sophisticated scheduling to optimize performance at the system level and on the underlying infrastructure. Run:ai enables enterprise customers to manage and optimize their compute infrastructure, whether on premises, in the cloud or in hybrid environments. The deal is valued at about $700 million.

Okian Warrior writes: For $10,000, you can now get a flamethrower mounted on a robotic dog. Just load the webpage and scroll down. I saw this on the news today. *Definitely* we need to have a conversation about where AI is going. The robot, called the Thermonator, is constructed by Ohio flame throwing manufacturer Throwflame and features one of the company's ARC flamethrowers mounted on its back. The 26-pound robotic quadruped "can shoot fire in a 30-foot stream and comes with a built-in fuel tank powered by gasoline," notes Gizmodo. "The company says the robot also has an hour-long battery, a laser sight, and lidar mapping, and it can be remotely controlled via the company's app."

The company says its product is designed for "wildfire control and prevention," "agriculture management," "ecological conservation," "entertainment and SFX," and "snow and ice removal." It can be yours for the low price of $9,420 with free shipping.

An anonymous reader quotes a report from the New York Times: Generative A.I. technologies can write poetry and computer programs or create images of teddy bears and videos of cartoon characters that look like something from a Hollywood movie. Now, new A.I. technology is generating blueprints for microscopic biological mechanisms that can edit your DNA, pointing to a future when scientists can battle illness and diseases with even greater precision and speed than they can today. Described in a research paper published on Monday by a Berkeley, Calif., startup called Profluent, the technology is based on the same methods that drive ChatGPT, the online chatbot that launched the A.I. boom after its release in 2022. The company is expected to present the paper next month at the annual meeting of the American Society of Gene and Cell Therapy. "Its OpenCRISPR-1 protein is built on a similar structure as the fabled CRISPR-Cas9 DNA snipper, but with hundreds of mutations that help reduce its off-target effects by 95%," reports Fierce Biotech, citing the company's preprint manuscript published on BioRxiv. "Profluent said it can be employed as a 'drop-in replacement' in any experiment calling for a Cas9-like molecule."

While Profluent will keep its LLM generators private, the startup says it will open-source the products of this initiative. "Attempting to edit human DNA with an AI-designed biological system was a scientific moonshot," Profluent co-founder and CEO Ali Madani, Ph.D., said in a statement. "Our success points to a future where AI precisely designs what is needed to create a range of bespoke cures for disease. To spur innovation and democratization in gene editing, with the goal of pulling this future forward, we are open-sourcing the products of this initiative."

The Ray-Ban Meta Smart Glasses now feature support for multimodal AI -- without the need for a projector or $24 monthly fee. (We're looking at you, Humane AI.) With the new update, the Meta AI assistant will be able to analyze what you're seeing, and it'll give you smart, helpful answers or suggestions. The Verge reports: First off, there are some expectations that need managing here. The Meta glasses don't promise everything under the sun. The primary command is to say "Hey Meta, look and..." You can fill out the rest with phrases like "Tell me what this plant is." Or read a sign in a different language. Write Instagram captions. Identify and learn more about a monument or landmark. The glasses take a picture, the AI communes with the cloud, and an answer arrives in your ears. The possibilities are not limitless, and half the fun is figuring out where its limits are. [...]

To me, it's the mix of a familiar form factor and decent execution that makes the AI workable on these glasses. Because it's paired to your phone, there's very little wait time for answers. It's headphones, so you feel less silly talking to them because you're already used to talking through earbuds. In general, I've found the AI to be the most helpful at identifying things when we're out and about. It's a natural extension of what I'd do anyway with my phone. I find something I'm curious about, snap a pic, and then look it up. Provided you don't need to zoom really far in, this is a case where it's nice to not pull out your phone. [...]

But AI is a feature of the Meta glasses. It's not the only feature. They're a workable pair of livestreaming glasses and a good POV camera. They're an excellent pair of open-ear headphones. I love wearing mine on outdoor runs and walks. I could never use the AI and still have a product that works well. The fact that it's here, generally works, and is an alright voice assistant -- well, it just gets you more used to the idea of a face computer, which is the whole point anyway.

A lawsuit is alleging Amazon was so desperate to keep up with the competition in generative AI it was willing to breach its own copyright rules. From a report: The allegation emerges from a complaint accusing the tech and retail mega-corp of demoting, and then dismissing, a former high-flying AI scientist after it discovered she was pregnant. The lawsuit was filed last week in a Los Angeles state court by Dr Viviane Ghaderi, an AI researcher who says she worked successfully in Amazon's Alexa and LLM teams, and achieved a string of promotions, but claims she was later suddenly demoted and fired following her return to work after giving birth. She is alleging discrimination, retaliation, harassment and wrongful termination, among other claims.

An anonymous reader shares a report: For years, people who have found Google search frustrating have been adding "Reddit" to the end of their search queries. This practice is so common that Google even acknowledged the phenomenon in a post announcing that it will be scraping Reddit posts to train its AI. And so, naturally, there are now services that will poison Reddit threads with AI-generated posts designed to promote products.

A service called ReplyGuy advertises itself as "the AI that plugs your product on Reddit" and which automatically "mentions your product in conversations naturally." Examples on the site show two different Redditors being controlled by AI posting plugs for a text-to-voice product called "AnySpeech" and a bot writing a long comment about a debt consolidation program called Debt Freedom Now. A video demo shows a dashboard where a user adds the name of their company and URL they want to direct users to. It then auto-suggests keywords that "help the bot know what types of subreddits and tweets to look for and when to respond."

Moments later, the dashboard shows how Reply Guy is "already in the responses" of the comments section of different Reddit posts. "Many of our responses will get lots of upvotes and will be well-liked." The creator of the company, Alexander Belogubov, has also posted screenshots of other bot-controlled accounts responding all over Reddit. Begolubov has another startup called "Stealth Marketing" that also seeks to manipulate the platform by promising to "turn Reddit into a steady stream of customers for your startup."

prisoninmate writes: Fedora Linux 40 distribution has been officially released -- powered by the latest Linux 6.8 kernel series, and featuring the GNOME 46 and KDE Plasma 6 desktop environments, reports 9to5Linux:

"Powered by the latest and greatest Linux 6.8 kernel series, the Fedora Linux 40 release ships with the GNOME 46 desktop environment for the flagship Fedora Workstation edition and the KDE Plasma 6 desktop environment for the Fedora KDE Spin, which defaults to the Wayland session as the X11 session was completely removed."

"Fedora Linux 40 also includes some interesting package management changes, such as dropping Delta RPMs and disabling support in the default configuration of DNF / DNF5. It also changes the DNF behavior to no longer download filelists by default. However, this release doesn't ship with the long-awaited DNF5 package manager. For AMD GPUs, Fedora Linux 40 ships with AMD ROCm 6.0 as the latest release of AMD's software optimized for AI and HPC workload performance, which enables support for the newest flagship AMD Instinct MI300A and MI300X datacenter GPUs."

Microsoft has launched Phi-3 Mini, a lightweight AI model with 3.8 billion parameters, as part of its plan to release three small models. Phi-3 Mini, trained on a smaller data set compared to large language models, is available on Azure, Hugging Face, and Ollama. Microsoft claims Phi-3 Mini performs as well as models 10 times its size, offering capabilities similar to GPT-3.5 in a smaller form factor. Smaller AI models are more cost-effective and perform better on personal devices.

According to French business magazine Challenges, Apple has acquired Datakalab -- a Paris-based startup specializing in artificial intelligence compression and computer vision technology. 9to5Mac reports: Datakalab described itself as "experts in low power, runtime efficient, and deep learning algorithms" that work on device. On its LinkedIn page, Datakalab highlights "industry leading compression and adaptation to deploy embedded computer vision that is fast, cost-effective and precise." Prior to the Apple acquisition had between 10 and 20 employees.

From Datakalab's now-defunct website: "Datakalab is a French technology company that develops computer image analysis algorithms to measure flows in public space. The images are instantly transformed into anonymized statistical data processed locally in 100ms. Datakalab does not store any images or personal data and only keeps statistical data. Datakalab products are built according to the principle of 'Privacy by Design.'"

While neither Apple nor DatakaLab have acknowledged the acquisition, Challenges says that the deal was reported to the European Commission this month. The report says that Datakalab's two founders did not join Apple, but multiple other employees did make the jump. Datakalab also held multiple patents related to AI compression and vision technology. The acquisition makes perfect sense given Apple's rumored ambitions to run its upcoming AI-related features in iOS 18 "entirely on device."

An anonymous reader shares a report: To accommodate tech companies' pivots to artificial intelligence, tech companies are increasingly investing in ways to power AI's immense electricity needs. Most recently, OpenAI CEO Sam Altman invested in Exowatt, a company using solar power to feed data centers, according to the Wall Street Journal. That's on the heals of OpenAI partner, Microsoft, working on getting approval for nuclear energy to help power its AI operations. Last year Amazon, which is a major investor in AI company Anthropic, said it invested in more than 100 renewable energy projects, making it the "world's largest corporate purchaser of renewable energy for the fourth year in a row."

Long-time Slashdot reader tippen shared this report from the Register: AI agents, which combine large language models with automation software, can successfully exploit real world security vulnerabilities by reading security advisories, academics have claimed.

In a newly released paper, four University of Illinois Urbana-Champaign (UIUC) computer scientists — Richard Fang, Rohan Bindu, Akul Gupta, and Daniel Kang — report that OpenAI's GPT-4 large language model (LLM) can autonomously exploit vulnerabilities in real-world systems if given a CVE advisory describing the flaw. "To show this, we collected a dataset of 15 one-day vulnerabilities that include ones categorized as critical severity in the CVE description," the US-based authors explain in their paper. "When given the CVE description, GPT-4 is capable of exploiting 87 percent of these vulnerabilities compared to 0 percent for every other model we test (GPT-3.5, open-source LLMs) and open-source vulnerability scanners (ZAP and Metasploit)...."

The researchers' work builds upon prior findings that LLMs can be used to automate attacks on websites in a sandboxed environment. GPT-4, said Daniel Kang, assistant professor at UIUC, in an email to The Register, "can actually autonomously carry out the steps to perform certain exploits that open-source vulnerability scanners cannot find (at the time of writing)."
The researchers wrote that "Our vulnerabilities span website vulnerabilities, container vulnerabilities, and vulnerable Python packages. Over half are categorized as 'high' or 'critical' severity by the CVE description...."

"Kang and his colleagues computed the cost to conduct a successful LLM agent attack and came up with a figure of $8.80 per exploit"

Remember when Apple filed a lawsuit against chip startup Rivos (saying that in one year Rivos hired more than 40 former Apple employees to work on competing system-on-a-chip technology)? Apple settled that suit in February.

And now Tuesday Rivos announced that it raised $250 million, according to Reuters, "in a funding round that will enable it to manufacture its first server chip geared for artificial intelligence," combining a CPU with an AI-accelerating component optimized for LLMs and data analytics. Nvidia gobbled up more than 80% market share of AI chips in 2023. But a host of startups and chip giants have started to launch competing products, such as Intel's Gaudi 3 and Meta's inference chip — both unveiled last week. Rivos is tight-lipped about the specifics of the product, but has disclosed that its plans include designing chips based on the RISC-V architecture, which is an open source alternative to the architectures made by Arm, Intel, and Advanced Micro Devices.. [U]sing the open source alternative means Rivos does not have to pay a license fee to Arm. "RISC-V doesn't have a (large) software ecosystem, so I decided to form a company and then build software-defined hardware — just like what CUDA did with Nvidia," said Lip-Bu Tan, founding managing partner at Walden Catalyst, one of Rivos' investors.
Meanwhile, there's a rumor that Allen Wu, former chief executive of Arm China, has founded a new company that will develop chips based on RISC-V. Tom's Hardware writes: Under the leadership of the controversial Allen Wu, Zhongzhi Chip is reportedly attracting a notable influx of talent, including numerous former employees of Arm, indicating the new company's serious ambitions in the chip sector... [T]he company's operational focus remains partially unclear, with speculation around whether it will primarily engage in its own R&D initiatives or represent Tenstorrent in China as its agent... which develops HPC CPUs and AI processors based on the RISC-V ISA... Based on the source report, Zhongzhi Chip is leveraging its connections and forming alliances with several other leading global RISC-V chip developers.

Earlier this week, Netflix found itself embroiled in an AI scandal when Futurism spotted AI-generated images used in the Netflix documentary What Jennifer Did.. The movie's credits do not mention any uses of AI, causing critics to call out the filmmakers for "potentially embellishing a movie that's supposed to be based on real-life events," reports Ars Technica. An executive producer of the Netflix hit acknowledged that some of the photos were edited to protect the identity of the source but remained vague about whether AI was used in the process. From the report: What Jennifer Did shot to the top spot in Netflix's global top 10 when it debuted in early April, attracting swarms of true crime fans who wanted to know more about why Pan paid hitmen $10,000 to murder her parents. But quickly the documentary became a source of controversy, as fans started noticing glaring flaws in images used in the movie, from weirdly mismatched earrings to her nose appearing to lack nostrils, the Daily Mail reported, in a post showing a plethora of examples of images from the film. [...]

Jeremy Grimaldi -- who is also the crime reporter who wrote a book on the case and provided the documentary with research and police footage -- told the Toronto Star that the images were not AI-generated. Grimaldi confirmed that all images of Pan used in the movie were real photos. He said that some of the images were edited, though, not to blur the lines between truth and fiction, but to protect the identity of the source of the images. "Any filmmaker will use different tools, like Photoshop, in films," Grimaldi told The Star. "The photos of Jennifer are real photos of her. The foreground is exactly her. The background has been anonymized to protect the source." While Grimaldi's comments provide some assurance that the photos are edited versions of real photos of Pan, they are also vague enough to obscure whether AI was among the "different tools" used to edit the photos.

Linus Torvalds, discussing the AI hype, in a conversation with Dirk Hohndel, Verizon's Head of the Open Source Program Office: Torvalds snarked, "It's hilarious to watch. Maybe I'll be replaced by an AI model!" As for Hohndel, he thinks most AI today is "autocorrect on steroids." Torvalds summed up his attitude as, "Let's wait 10 years and see where it actually goes before we make all these crazy announcements."

That's not to say the two men don't think AI will be helpful in the future. Indeed, Torvalds noted one good side effect already: "NVIDIA has gotten better at talking to Linux kernel developers and working with Linux memory management," because of its need for Linux to run AI's large language models (LLMs) efficiently.

Torvalds is also "looking forward to the tools actually to find bugs. We have a lot of tools, and we use them religiously, but making the tools smarter is not a bad thing. Using smarter tools is just the next inevitable step. We have tools that do kernel rewriting, with very complicated scripts, and pattern recognition. AI can be a huge help here because some of these tools are very hard to use because you have to specify things at a low enough level." Just be careful, Torvalds warns of "AI BS." Hohndel quickly quipped, "He meant beautiful science. You know, "Beautiful science in, beautiful science out."