Artificial Intelligence - Page 34

Geekbench AI 1.0 is here, after years of feedback and test iteration with its customers, partners, and the AI engineering community, Primate Labs is proud to announce its latest machine learning benchmark is now ready, and it has a new name: Geekbench AI. You can download Geekbench AI 1.0 here.

Geekbench AI is a new benchmarking suite with a testing methodology for machine learning, deep learning, and AI-centric workloads, all with the same cross-platform utility and real-world workload reflection that Primate Labs' benchmarking software (Geekbench, duh) is known for.

The developer explains on its website: "Measuring performance is, put simply, really hard. That's not because it's hard to run an arbitrary test, but because it's hard to determine which tests are the most important for the performance you want to measure - especially across different platforms, and particularly when everyone is doing things in subtly different ways. At Primate Labs, we build our tests to reflect the sort of use cases that developers build their applications to do through detailed and ongoing conversations with software and hardware engineers across the industry, rather than just crunching basic math for hours".

SoftBank was talking with Intel about making an AI chip that would compete with NVIDIA's dominant AI GPUs, but the plan "floundered" after Intel failed to meet the requirements of Japan's SoftBank.

In a new report from the Financial Times, we're hearing that negotiations to partner with Intel would've rapidly accelerated SoftBank's efforts to combine the chip design of its "crown jewel" as the FT puts it: Arm. Japan's SoftBank owns Arm Holdings, so with its Arm architecture and Intel fabbing the chip with SoftBank's production expertise of its latest acquisition -- Graphcore -- according to "people familiar with the matter".

SoftBank boss Masayoshi Son plans to dump billions of dollars into putting Japan at the center of the AI boom, where the Arm owner wants to create a rival to NVIDIA's dominant AI GPUs. Son has pitched his ideas to the usual Big Tech companies, with chip production and software through to providing power for the data centers that would be powered by its chips.

Samsung's new 8-layer HBM3E memory has passed NVIDIA's qualification tests to be used in its AI GPUs.

In a new report from Reuters, the outlet says that the qualification clears a "major hurdle" for Samsung -- which is the world's largest memory manufacturer -- and has been struggling to catch up to South Korean rival, SK hynix, which has been providing its bleeding-edge HBM3E memory to NVIDIA for its AI GPUs.

Samsung still hasn't signed a supply deal for the approved 8-layer HBM3E memory chips with NVIDIA, but "will do so soon" according to Reuters' sources, who declined to be identified as the matter remains confidential. The new 8-layer HBM3E memory ships from Samsung would be supplied to NVIDIA in Q4 2024, which is not far away now.

The world of AI PCs is just beginning with the first waves of Copilot+ ready PCs out in the wild, with 14% of PCs shipped globally in Q2 2024 featuring an NPU, making them an AI PC.

In a new report from Canalys, we're learning that 8.8 million AI-capable PCs were shipped in Q2 2024, with each of those 8.8 million systems featuring the latest AI processor (with an NPU) from AMD, Apple, Intel, and Qualcomm. As we see new generations of AI processors from AMD and Intel, Canalys says that we can expect rapid growth in the second half of this year, and going into high gear in 2025.

If we look at just the Windows segment, AI-capable PC shipments surged 127% sequentially in Q2 2024, with Lenovo shipping out its Qualcomm Snapdragon X Elite-based Copilot+ PCs with the Yoga Slim 7x and ThinkPad T14s, boosting its AI PC market share to around 6% of all Windows PC shipments, a mammoth 228% growth. HP followed behind Lenovo with a 7% share of AI PCs.

It looks like there is a "component shortage" for NVIDIA's new Blackwell-based GB200 AI servers, with market demand in Taiwan at the highest levels because of the AI market needing as many chips as possible.

In a new report from Taiwan Economic Daily, we're learning that NVIDIA's new GB200 AI servers are experiencing huge development issues, with the main problem stemming from leaks from the liquid cooling system inside of the next-generation multi-million-dollar AI server.

The water leakage inside of a GB200 AI server would be a disaster as you can imagine, with Taiwanese manufacturers moving into emergency mode to solve it, with new Taiwanese suppliers stepping up to help NVIDIA get its GB200 AI servers to market.

SK hynix has just announced it's planning to develop a 4F2 (square) DRAM, joining South Korean rival Samsung and its journey into the world of 3D DRAM.

The cost of EUV (extreme lithography) processes has continued to skyrocket since the commercialization of 1c DRAM, with SK hynix researcher Seo Jae Wook noted during an industry conference in Seoul, South Korea, on Monday.

The Elec reports that Seo said at the time whether manufacturing DRAM this way (using EUV) was profitable, where in response, SK hynix said it was considering manufacturing vertical gate (VG) or 3D DRAM for future DRAM. VG is what SK hynix internally calls 4F2, while Samsung calls theirs vertical channel transistor (VCT).

Last month we reported on AMD's announcement that it was acquiring the largest private AI lab in Europe - Silo AI. Today, AMD has followed up on the announcement to confirm that the "all-cash transaction valued at approximately $665 million" has now been completed, with Silo AI's scientists and engineers now a part of the AMD family.

$665 million in cash is nothing to sneeze at, and for AMD, the acquisition is the latest step in the company's broader pivot that puts its main focus on AI and AI-related technologies. This is nothing new; we've seen the same shift happen in other companies like Google, Meta, Apple, and, of course, NVIDIA. However, NVIDIA's AI focus started many years ago.

"AI is our number one strategic priority," said Vamsi Boppana, AMD senior vice president, AIG. "We continue to invest in both the talent and software capabilities to support our growing customer deployments and roadmaps."

GPU VRAM modding isn't new, but Chinese cloud companies are adding copious amounts of VRAM to the likes of the GeForce RTX 4090D (24GB modded to 48GB) and the RTX 4080 SUPER from 16GB to 32GB and renting them out at an hourly rate.

Now, we've got a Chinese AI expert that is talking with people in the country about selling NVIDIA's new GeForce RTX 4090D graphics card -- but with double the VRAM, from 24GB to 48GB of GDDR6X -- as well as the GeForce RTX 4080 SUPER upgraded from 16GB to 32GB of GDDR6X memory.

The source says that the GPUs are popular with cloud computing companies, as they're renting out the spare AI computing power because the demand is so high right now. The modded GeForce RTX 4080 SUPER with 32GB of VRAM is available for just $0.03 per hour, which is a damn good price for a monster modded RTX 4080 SUPER with 32GB of GDDR6X memory for AI workloads.

South Korea's memory chip exports to Taiwan surged over 225% year-over-year, thanks to the unstoppable demand of AI GPUs and AI accelerators and their respective HBM memory chips.

In a new report from the Korea Times, we're learning that outbound shipments of HBM memory chips to Taiwan reached $4.26 billion in the first 6 months of this year, up an incredible 225.7% from a year ago, "far outperforming" South Korea's overall increase of memory chip exports at 88.7%, according to data compiled by the industry ministry and the Korea International Trade Association.

Taiwan was the third-largest importer of South Korean memory chips in the period, pushing out both Vietnam and the United States. Market watchers said that the huge surge in memory chip exports to Taiwan is thanks to SK hynix's fantastic HBM supply to NVIDIA, which uses its HBM memory inside of its AI GPUs, and fabs its chips over at TSMC in Taiwan.

NEO Semiconductor has just unveiled the development of its new 3D X-AI chip technology, which aims to replace DRAM chips inside of HBM to solve data bus bottlenecks, by enabling AI processing through 3D DRAM.

The new 3D X-AI chip technology can reduce the huge amount of data transferred between HBM and GPUs during AI workloads, with NEO's innovative new 3D X-AI chip technology set to "revolutionize the performance, power consumption, and cost of AI chips for AI applications like generative AI".

NEO's new 3D X-AI chip technology has 100x the performance with 8000 neuron circuits to perform AI processing in 3D memory, a huge 99% power reduction that minimizes the requirement of transferring data to the GPU for calculation, reducing power consumption and heat generation by the data bus, and 8x the memory density with 300 memory layers, allowing HBM to store larger AI models.

When it comes to AI training and dealing with large data sets and increasingly complex large language models (LLMs) like Llama 70b, it's not simply a matter of being able to throw GPU horsepower at the problem until you find a solution. At least, it shouldn't be.

Phison's aiDAPTIV+ is a hybrid software and hardware solution for LLM training. It integrates Phison's Pascari A100 M.2 SSDs into a complete solution with linear scaling. Impressive! According to Phison, it unlocks access to run workloads previously reserved for data centers on a single workstation or server - supporting up to Llama-3 70B and Falcon 180B.

Phison's chart showcases the capabilities of aiDAPTIV+. Above, you can see a single system with the same configuration: four RTX 6000 Ada GPUs, 192GB of GDDR6 memory, and an additional 512GB of RAM. Phison's aiDAPTIVLink middleware extends this GPU memory capacity with two 2TB SSDs, paving the way for massive model support with low latency. This is impressive stuff, and it won the "Best of Show, Most Innovative AI Application" award at FMS: the Future of Memory and Storage.

It was only last month we heard about Apple, NVIDIA and many other big name players in the AI race being caught up in an investigative report that found they all used a public data set containing YouTube video transcripts to train their respective AI products, which is a violation of YouTube's terms-of-service (TOS).

YouTube has said in the past that any "unauthorized scraping or downloading of YouTube content" is strictly prohibited, and it's especially prohibited when that data is then used for commercial projects. Last month, a Proof News investigation found NVIDIA, Apple, and other AI companies used an academic data set containing subtitles from more than 170,000 YouTube videos to train AI models, and now NVIDIA has been caught in the spotlight again with a report from 404 Media.

According to the publication that spoke with a former NVIDIA employee about the company's internal processes, employees were instructed to scrape videos from Netflix, YouTube, and other sources to add to the data sets that are being used to an AI model for NVIDIA's Omniverse 3D world generator, self-driving car systems, a "digital human" AI avatar product, and the Cosmos deep learning model.

Dell announced its company is "getting leaner" with executives informing thousands of employees via a memo it has begun its effort into "streamlining layers of management."

President of global sales and customer operations Bill Scannell and global channels president John Byrne explained in the memo the company is attempting to grow faster in the market by concentrating its efforts on the development of "modern IT and AI" and that it can seemingly achieve that without 10% of it workforce, or approximately 12,500 employees. The layoffs are part of Dell's overall push to reduce its workforce to under 100,000 people.

These layoffs at Dell come only a matter of days after Intel announced it was laying off 15% of its workforce, amounting to 15,000 job cuts and a 26% stock drop. The massive stock drop is attributed to recently confirmed hardware issues with Raptor Lake chips, which is causing a fire internally for the CPU manufacturer. As for Dell, last year, the company planned on reducing its workforce by 5% but ended up reducing it by double that, or 13,000 people.

Since the explosion of AI-powered models, academics, teachers, and many other professions have been rightfully concerned about tools such as ChatGPT being used to assist in the writing of essays and research papers.

The easy accessibility to powerful AI models such as ChatGPT has given rise to a substantial increase in the amount of AI-generated content across the internet. Unfortunately, it appears some of this content has already made its way into scientific journals within submitted papers, and classrooms with students taking advantage of these free tools to write assignments and papers.

To prevent the abuse of this technology in the academic setting, companies rolled out AI detection tools. Unfortunately, these detection tools proved unreliable, but according to a new article by The Washington Post, OpenAI, the creators of ChatGPT, have developed a new method that can detect ChatGPT-generated content with a 99.9% accuracy rate. The new system issues a watermark to ChatGPT-generated content that cannot be seen by the human user but detected by the detection too.

NVIDIA's next-generation Blackwell AI GPU has been reportedly experiencing some issues, which have caused some major delays that will see shipments kicking off in 2025... except for Foxconn.

Foxconn is the only company that has received enough of NVIDIA's new Blackwell GB200 Superchips, so it will be the only company pumping out new GB200 AI servers. According to UDN, they will be available in Q4 2024.

NVIDIA's new GB200 AI servers were meant to be shipping in large quantities in Q4 2024, but the yield issues with B200 forcing a redesign for B200A this time next year, is causing some major headaches for some of the biggest companies on the planet. UDN reports that it was found that the problem could stem from "unsatisfactory" yield rates of the advanced packaging required for GB200.

Elon Musk has said he wants to "give people superpowers" with his brain-computer interface (BCI) implants through Neuralink, which the SpaceX and Tesla founder said will let you "outperform a pro gamer".

Elon wants to increase humans' "output rate." With Neuralink's BCI, he said that there's the potential to have "three, maybe six, maybe more orders of magnitude" of how fast our brain processes signals to the chip.

The SpaceX and Tesla boss sat down for the latest episode of the Lex Fridman podcast, with Fridman saying there would be "hundreds of millions" of people getting Neuralink implants in the "next couple of decades" to which Elon agreed.

Stability AI's Stable Diffusion 3 is the latest version of its popular and powerful AI image-generation tool. It can deliver photorealistic results thanks to what it describes as the "most advanced text-to-image open model yet." For those following the rise of AI image generators, one thing that Stable Diffusion 3 brings to the table - or solves - is the ability to recreate repeating patterns and, yes, human hands.

It's impressive, and the model runs on hardware ranging from an Apple M2 Ultra to a GeForce RTX 4090-powered rig. Naturally, with its 24GB of GDDR6X memory and unlocked Ada Lovelace power, the latter is several magnitudes faster than any other "at-home" option. Still, with TensorRT acceleration and optimization, the GPU can render or generate images in real-time.

You can see this in action in NVIDIA's video, which it presented at SIGGRAPH 2024. The video showcases SDXL Turbo generating an image of "a hot rod, racing in the desert at sunset" in real-time, adding details to the image like adding a canyon to the background as it's being typed in. Impressive!

On August 8 the NFL will roll out new facial recognition technology across its thirty-two stadiums located in various states.

The new facial recognition software is called Wicket and it's powered by an artificial intelligence. The new system is designed with the goal of decreasing the time it takes people to get in and out of stadiums, verifying credentials, and enabling staff to move more easily around stadiums. Notably, the software is primarily designed to assist credentialed officials in verifying their identify at restricted areas, and to prevent any fraudulent use of counterfeit physical credientials.

As for ticketholders, some teams have extended the technology to customers, which will require customers to link their ticketing account to their facial image selfie. The Wicket software will create a unique digital code that represents a customer's facial features instead of storing an actual image of a person.

NVIDIA has hit some major roadblocks with its new Blackwell AI GPUs, with redesigns in the works, and a new B200A on the way... but in the middle of this mess, we get some new details on the specs of Blackwell Ultra.

NVIDIA first teased its mid-generation refresh "Blackwell Ultra" earlier this year, as well as its next-gen Rubin R100 AI GPU that will feature ultra-fast HBM4 memory in 2025 (if there's no delays for Rubin, as there are with Blackwell).

SemiAnalysis has the scoop here, with Blackwell Ultra acting as a mid-generaiton enhancement of Blackwell, with the standard CoWoS-L Blackwell Ultra known as "B210" or "B200 Ultra". Inside, NVIDIA's new Blackwell Ultra features both a memory refresh -- up to 288GB of 12-Hi HBM3E memory -- and performance enhancements of up to 50% in FLOPS.

NVIDIA is reportedly experiencing some major issues with its new Blackwell AI GPUs, with the new B100 and B200 AI GPU shipments heavily impacted, with design flaws causing major headaches not just for NVIDIA.

In a new report published by SemiAnalysis, the outlet reports that there are issues with the Blackwell die needing a possible redesign or that the bridge dies inside TSMC's new CoWoS-L advanced packaging needs a redesign.

The result? NVIDIA is now reportedly working on the B200A AI GPU, which will be released towards the second half of 2025 and won't have the issues that are now plaguing the fastest AI GPU before it could hit the market.