Artificial Intelligence - Page 5

Phison is expanding its aiDAPTIV+ software to the NVIDIA Jetson platform, enabling enhanced generative AI inference at the edge of robotics development.

Phison has created a specialized SSD for the NVIDIA Jetson platform and has integrated its aiDAPTIVE+ software to enable Fine-Tune training, which allows users to take an AI model and add their own data into the model. The idea behind this integration is to reduce the performance cost of running the AI by offloading some of the processing from the GPU VRAM over to the SSD.

Phison explained to me that with these upgrades to the Jetson platform they are able to provide up to 14x improvement on Time to First Token (TTFT), which is the time it takes for an AI to provide a response to a question. Moreover, these changes also increased the token length by 8x, which is the length of the response generated by the AI. Ultimately, Phison's improvements made to Jetson have unlocked the platform in a way that enables faster responses with a greater length, enhancing the quality of the AI chat.

Bots in competitive or cooperative multiplayer games have been a problem for years, with a new study from Echelon Insights stating that 59% of gamers have encountered third-party bots in games. And with that, 71% agree that bots make it less fun to play certain games, with 77% agreeing that it's essential to verify that you are a human before jumping into the action. And these bots are getting increasingly sophisticated in the age of AI gaming.

'Razer ID verified by World ID' is one solution to this problem, and it's set to be part of the upcoming multiplayer game TOKYO BEAST. The game is set in Tokyo in the year 2124, a time when humans and "advanced autonomous androids" coexist. It's a competitive title that includes collectible unique NFTs alongside in-game purchases via Razer.

'Razer ID verified by World ID' is powered by secure, single sign-on (SSO) technology designed to verify "real human gamers" to create a more authentic and immersive gaming experience. World ID, a company co-founded by Sam Altman and Alex Blania, is all about confirming someone's unique online human identity with a focus on privacy. It can tell that someone is human without knowing who they are.

With new AI chatbots released every week and new models seemingly by the day, it's an uncertain time to be a computer programmer - or consider entering the field. AI-assisted coding tools, from GitHub Copilot to ChatGPT-powered development, are capable of generating full applications with minimal human input. As automation advances, some question whether traditional programming skills will remain relevant.

Andrew Ng, the founder of DeepLearning AI and co-founder of Google Brain, Coursera, and an active Stanford professor, takes a different view. In a recent blog post, he argued that this is actually the best time to learn to code, dismissing claims that AI will make programming obsolete.

With the emergence of AI tools affecting almost every industry, few are more affected than the field of software development. 'Vibe coding' is one of the trends to emerge from that shift, and we'll go into what it is, and how it's affecting these industries.

To start at the beginning - in February 2025, OpenAI co-founder and former Tesla AI lead Andrej Karpathy coined the term on X. In a widely publicized post, he describes it as a method that essentially involves letting go of the intricacies of generated code - and essentially 'fully giving in' to the vibes. In other words, embracing an intuitive, instinctual approach to writing programs - and forgetting about understanding the code itself.

In practice, what this looks like is a conversational approach to software development. As Karpathy describes, it's giving the chatbot simple, almost dumb, 'vibe driven' prompts - and letting the AI generate beyond your comprehension. For example, a user might prompt an AI coding assistant with something as vague as "Make a flight simulator where you can buy an F-16" and let the AI generate the bulk of the game's code, or "Fix the UI so it looks cleaner, but keep the aesthetic fun." Instead of making manual adjustments, vibe coders just keep iterating with broad prompts like "Make the sidebar padding feel right" or "Tweak the animations so they pop more." The AI takes over, handling all the changes while the coder simply approves or rejects based on vibes alone.

NVIDIA is hosting its GPU Technology Conference (GTC) event next week, where we'll be introduced to its beefed-up GB300 "Blackwell Ultra" AI GPUs, new details on its next-gen Rubin R100 AI GPU which will feature next-gen HBM4 memory, new CPO technology, and more.

JP Morgan's outlook for NVIDIA GTC 2025 has Blackwell Ultra GB300 as the highlight of the show, with the new GB300 AI chip featuring a logic structure similar to B200 but with huge capacity increases on HBM and massive increases in power consumption.

NVIDIA's new GB300 Blackwell Ultra AI GPU will have up to 288GB of 12-Hi HBM3E memory, and a thermal design power (TDP) that has been increased up to 1.4kW. We are to expect a major performance boost from GB300 of up to 50% faster than GB200 in FP4 computing performance, and JP Morgan expects GB300 to start shipping in Q3 2025.

Apple launched its new M3 Ultra processor inside of its new Mac Studio earlier this week, packing a 32-core CPU and 80-core GPU and boy-oh-boy does it perform well with DeepSeek R1 models.

In a new video from YouTuber Dave2D, who has compared Apple's new M3 Ultra against the M2 Ultra, M4 Max, and M3 Air processors, the M3 Ultra absolutely destroys DeepSeek R1 performance. The YouTuber uses DeepSeek R1 and i ts 7B, 14B, and 32B parameter models first, which the M3 Ultra takes the crown (by far) in all tests.

Apple's new M3 Ultra (which is pretty much just 2 x M3 Max chips acting as one) has up to 512GB of unified RAM support, compared to the 128GB on M2 Ultra + M4 Max, and just 24GB on the M3 Air. This leads the Apple M3 Ultra to pump out 89.07 T/s on DeepSeek R1 with 7B parameters, compared to 54.22 T/s on the M2 Ultra, 53.18 T/s on the M4 Max, and just 17.7 T/s on the M3 Air.

In a breakthrough for archaeology, scientists are using artificial intelligence and Synthetic Aperture Radar (SAR) to uncover traces of 5,000-year-old civilizations in Dubai and medieval sites in Mongolia, revealing lost histories buried beneath desert sands.

As reported by Daily Galaxy, AI and SAR imaging have revealed 5,000-year-old settlements and pathways in Dubai, providing insight into how early civilizations thrived in harsh desert conditions. Similarly, in Mongolia, the same technology uncovered thousands of potential medieval sites along the historic Silk Road - one of the most significant trade networks in human history.

The most notable aspect of these developments is uncovering ancient settlements without excavation. Detecting entire lost civilizations beneath the desert without traditional digging is a game-changer for archaeology.

The newer breed of deep reasoning models - designed to 'think' before answering - are also more open to taking any route possible to solve a given problem, it seems, even if that means cheating.

Researchers submitted a paper to Cornell university entitled 'Demonstrating specification gaming in reasoning models' which tested AIs playing games of chess on Stockfish.

They found that the new models, such as ChatGPT o1-preview and DeepSeek-R1, would "often hack the benchmark by default" - meaning resorting to cheating of one kind or another.

NVIDIA is expected to unveil its new GB300 AI GPUs at GTC 2025 later this month, with the huge shift into fully liquid-cooled AI clusters on its way.

In a new report from UDN, we're learning that the energy consumption of NVIDIA's new GB300 AI GPU has "increased significantly" from GB200, and that the heat dissipation demand is greater, which has set off a "second cooling revolution". No longer will more water-cooling plates be introduced, but the use of water-cooling quick connectors will increase 4x with GB300 compared to GB200.

NVIDIA's new GB300 AI GPUs will be fully water-cooled, with Taiwan cooling giants Shuanghong and Qihong to make "huge profits" says UDN, but we'll also see water-cooling quick connector suppliers like Fushida and Shishuo will also be a large part of this purported "second cooling revolution".

NVIDIA is preparing 64,000 of its new GB200 AI GPUs for OpenAI and Oracle to use in their expansive new Stargate AI supercomputer.

In a new report from Bloomberg, we're learning that NVIDIA's super-fast GB200 AI GPUs will be supplied for the Stargate AI supercomputer by the end of 2026 according to "a person familiar with the matter". These new GB200 chips will be added to multiple halls of the AI data center in phases, with the initial rollout of 16,000 GB200 AI GPUs to be provided by the summer.

The new Stargate AI supercomputer project was announced by President Trump along with OpenAI, Japan's SoftBank Group Corp., and Oracle at the White House in January 2025. An OpenAI spokesperson said the AI startup is working with Oracle on the design and delivery of the new data center that is destined for Abilene, Texas, USA, and that Oracle is in charge of getting and operating the Stargate supercomputer built there.