Intel has unveiled its Core Ultra 200V lineup, previously known as Lunar Lake, boasting superior AI performance, fast CPUs, and competitive integrated GPUs for thin laptops. The processors feature eight CPU cores, integrated memory, and enhanced efficiency but are limited to 32GB RAM. Major manufacturers like Acer, Asus, Dell, and HP will launch laptops with these new chips. Reviews are pending to confirm Intel's claims.

Microsoft will unveil its vision for AI PCs at an event in Seattle on May 20. The company is confident that its new Arm-powered Windows laptops will beat Apple's M3-powered MacBook Air in both CPU performance and AI-accelerated tasks. The laptops will feature Snapdragon X Elite processors from Qualcomm. Microsoft is planning to ship consumer models of its Surface Pro 10 and Surface Laptop 6 with Snapdragon X Elite processors instead of the Intel Core Ultra processors that the business-focused versions have.

Microsoft will unveil its vision for AI PCs at an event in Seattle on May 20. The company is confident that its new Arm-powered Windows laptops will beat Apple's M3-powered MacBook Air in both CPU performance and AI-accelerated tasks. The laptops will feature Snapdragon X Elite processors from Qualcomm. Microsoft is planning to ship consumer models of its Surface Pro 10 and Surface Laptop 6 with Snapdragon X Elite processors instead of the Intel Core Ultra processors that the business-focused versions have.

Microsoft will unveil its vision for AI PCs at an event in Seattle on May 20. The company is confident that its new Arm-powered Windows laptops will beat Apple's M3-powered MacBook Air in both CPU performance and AI-accelerated tasks. The laptops will feature Snapdragon X Elite processors from Qualcomm. Microsoft is planning to ship consumer models of its Surface Pro 10 and Surface Laptop 6 with Snapdragon X Elite processors instead of the Intel Core Ultra processors that the business-focused versions have.

AMD unveiled its latest AI processors, including the MI325X accelerator due in Q4 2024, at the Computex trade show. It also detailed plans to compete with Nvidia by releasing new AI chips annually. The MI350 series, expected in 2025, promises a 35-fold performance increase in inference compared to the MI300 series. The MI400 series is set for a 2026 release.

Intel has announced its new Gaudi 3 AI processors, claiming up to 1.7X the training performance, 50% better inference, and 40% better efficiency than Nvidia's H100 processors at a lower cost.

Intel has announced its new Gaudi 3 AI processors, claiming up to 1.7X the training performance, 50% better inference, and 40% better efficiency than Nvidia's H100 processors at a lower cost.

Microsoft recently spent an entire day pitting its new hardware against the MacBook Air. Its new Surface devices, equipped with Qualcomm's Snapdragon X Elite chips, pulled ahead in tests against Apple's category-leading laptop. Microsoft's Copilot Plus PCs feature an improved emulator that can emulate apps twice as fast as the previous generation of Windows on Arm devices. They are equipped with a neural processing unit that can perform more AI task operations per watt than the MacBook Air M3 and Nvidia's RTX 4060. Microsoft's Copilot Plus PCs will hit the market this summer.

Intel gave the first architectural details of its Gaudi 3 third-generation AI processor at Vision 2024 this week in Phoenix, Arizona. Gaudi 3 is made up of two identical silicon dies, each with a central region of 48 megabytes of cache memory, joined by a high-bandwidth connection, surrounded by four engines for matrix multiplication and 32 programmable units called tensor processor cores. It produces double the AI compute of Gaudi 2 using 8-bit floating-point infrastructure. It also provides a fourfold boost for computations using the BFloat 16 number format.

Intel gave the first architectural details of its Gaudi 3 third-generation AI processor at Vision 2024 this week in Phoenix, Arizona. Gaudi 3 is made up of two identical silicon dies, each with a central region of 48 megabytes of cache memory, joined by a high-bandwidth connection, surrounded by four engines for matrix multiplication and 32 programmable units called tensor processor cores. It produces double the AI compute of Gaudi 2 using 8-bit floating-point infrastructure. It also provides a fourfold boost for computations using the BFloat 16 number format.

Meta has announced the next generation of its AI accelerator chip. Its development focused on chip memory (128GB at 5nm) and throughput (11 TFLOPs at int8).

Nvidia's new Blackwell chip demonstrated top per GPU performance in MLPerf's LLM Q&A benchmark, showcasing significant advancements with its 4-bit floating-point precision. However, competitors like Untether AI and AMD also showed promising results, particularly in energy efficiency. Untether AI's speedAI240 chip, for instance, excelled in the edge-closed category, highlighting diverse strengths across new AI inference hardware.

Foxconn is reportedly assembling Apple AI servers that contain the M2 Ultra. It is planning to assemble AI servers powered by the M4 chip in late 2025. While Apple is prioritizing on-device processing for many of its upcoming AI tools, some operations will inevitably have to occur in the cloud. The company is expected to announce on-device AI features at WWDC in June. 2025's iPhone 17 models will apparently be more focused AI devices.

Apple unveiled the A18 and A18 Pro chips at its “Glowtime” event, promising significant CPU and GPU improvements over the A16 Bionic. The A18 Pro boasts enhanced memory bandwidth and upgraded image-processing capabilities. Both chips support advanced AI features, with the A18 Pro notably improving on-device model performance and thermal design for better gaming experiences.

Apple has announced its next-generation Apple Silicon chip, the M4, the company's first chip designed specifically for AI. Featuring a 3-nanometer architecture and debuting in the 2024 iPad Pro, the new chip boasts a 10-core CPU that is 50% faster than the M2 and a new Neural Engine capable of processing 38 trillion operations per second. It enhances applications that leverage AI, although specific AI features for iPadOS haven't been detailed yet.

Apple reportedly has ambitious plans to design its own artificial intelligence server processor using TSMC's 3nm node. TSMC's 3nm technology is one of the most advanced semiconductor processes available. A specialist AI server processor would allow Apple to tailor hardware specifically to its software needs, potentially leading to more powerful and efficient technologies. While Apple is rumored to be prioritizing on-device processing for many of its upcoming AI tools, some operations will inevitably have to occur in the cloud.

Google's new AI chip, Cloud TPU v5p, is now available. It boasts nearly triple the training speed for large language models compared to its predecessor, TPU v4. This release underscores Google's position in the AI hardware race alongside competitors like Nvidia. Google has also introduced the Google Axion CPU, based on Arm's chip infrastructure, promising better performance and energy efficiency.

Microsoft has announced the general availability of its Phi-3 models and introduced Phi-3-Silica, a small language model optimized for Neural Processing Units in Copilot+ PCs. Phi-3-Silica, with 3.3 billion parameters, offers fast local inferencing with low power consumption, marking a significant step in integrating advanced AI directly into Windows devices to enhance productivity and accessibility. It will be available in June.

BrainChip has introduced the Akida Pico, a new chip designed for ultra-low power AI inference, specifically targeting battery-powered devices. This innovation is part of the growing field of neuromorphic computing, which draws inspiration from the human brain's architecture and functioning. Steven Brightfield, the chief marketing officer of BrainChip, emphasizes that the design is tailored for power-constrained environments, where devices like smartwatches and mobile phones operate with limited energy resources. The Akida Pico is a miniaturized version of BrainChip's previous Akida design, consuming just 1 milliwatt of power or even less, depending on the application. This chip is aimed at the "extreme edge" market, which includes small user devices that face significant limitations in power and wireless communication capabilities. The Akida Pico joins other neuromorphic devices, such as Innatera’s T1 chip and SynSense’s Xylo, which have also been developed for edge applications. Neuromorphic computing mimics the brain's spiking nature, where computational units, referred to as neurons, communicate through electrical pulses called spikes. This method allows for energy-efficient processing, as power is consumed only when spikes occur. Unlike traditional deep learning models, which operate continuously, spiking neural networks can maintain an internal state, enabling them to process inputs based on both current and historical data. This capability is particularly advantageous for real-time signal processing, as highlighted by Mike Davies from Intel, who noted that their Loihi chip demonstrated significantly lower energy consumption compared to traditional GPUs in streaming applications. The Akida Pico integrates a neural processing engine, event processing units, and memory storage, allowing it to function independently in some applications or in conjunction with other processing units for more complex tasks. BrainChip has also optimized AI model architectures to minimize power usage, showcasing their efficiency with applications like keyword detection for voice assistants and audio de-noising for hearing aids or noise-canceling headphones. Despite the potential of neuromorphic computing, widespread commercial adoption has yet to be realized, partly due to the limitations of low-power AI applications. However, Brightfield remains optimistic about the future, suggesting that there are numerous use cases yet to be discovered, including speech recognition and noise reduction technologies. Overall, the Akida Pico represents a significant step forward in the development of energy-efficient AI solutions for small, battery-operated devices, with the potential to transform how these technologies are integrated into everyday applications.

Apple's new Apple Intelligence system will use Private Cloud Compute to ensure any data processed on its cloud servers is protected in a transparent and verifiable way. Many of Apple's generative AI models can run entirely on a device powered by an A17+ or M-series chip. When a bigger model is required to fulfill a generative AI request, Apple Intelligence only sends relevant data to complete the task to special Apple silicon servers. Customer data will not be saved for future server access or used to further train models. The server code used for Private Cloud Compute will be publicly accessible.

Intel failed to produce AI processors for SoftBank's Project Izanagi, leading SoftBank to explore a partnership with TSMC. Despite setbacks, SoftBank remains committed to challenging major AI players with its own hardware and data center ecosystem, potentially backed by significant investment from global partners. The move could strain SoftBank's relationship with Arm clients as it risks direct competition.

Microsoft launched three new models in its Phi series: Phi-3.5-mini-instruct, Phi-3.5-MoE-instruct, and Phi-3.5-vision-instruct, each addressing different AI tasks with impressive benchmark performances. These models are open source under the MIT License and available for developers on Hugging Face. Despite their smaller size compared to some counterparts, the Phi models have achieved near-state-of-the-art results, surpassing competitors like GPT-4o and Llama in certain benchmarks.

Californian startup Ebb Carbon plans to use seawater to remove tons of carbon dioxide from the air. Its pilot carbon dioxide removal plant, codenamed Project Macoma, could start operations as soon as this year. It will pump hundreds of thousands of liters of seawater every day, splitting the water into acidic and alkaline streams using an electrochemical process. The alkaline outflow mixes with carbon dioxide in ambient seawater to create bicarbonate, a stable way to store carbon. While the impact of the plant will be small, the process, if scaled up, could help mitigate the effects of climate change.

Microsoft's new specifications for OEMs building AI PCs includes a requirement that they must have a Copilot key. To be recognized as an AI PC, OEM partners must also provide a combination of hardware and software including a Neural Processing Unit (NPU), the latest CPUs and GPUs, and access to Copilot. It is unclear what OEMs will get in return for adhering to Microsoft's AI PC definition. Intel recognizes some laptops without the Copilot key as AI PCs due to their integrated NPUs.

This article contains an interview with David Luan, one of OpenAI's early hires, a past leader of Google's LLM efforts and co-leader of Google Brain, and founder of Adept, one of the leading companies in the AI agents space, where he discusses his time with early OpenAI and how Adept is building agents that can do anything humans can do on a computer. Google had a huge lead with AI in 2017, but it was OpenAI that ended up making GPT 1/2/3. While Google's team created Transformers, the company's internal processes made it difficult for its researchers to get work done. OpenAI was able to beat Google because it took big swings and focused.

Apple's Worldwide Developers Conference will start with a keynote on June 10 and run through until June 14. This year's event should be similar to previous years, with announcements likely focusing on the company's fall software updates and new hardware. Apple has reportedly spent millions per day training its own AI models and it has been rumored to be courting news outlets for training content partnerships. The company may be planning a deal with third parties to supply cloud-based AI features. It may also be planning to open up an ecosystem for AI developers to create deep integrations into its devices.

Nvidia is developing a new AI chip, the B20, tailored to comply with U.S. export controls for the Chinese market, leveraging its partnership with distributor Inspur. Its advanced H20 chip has reportedly seen a rapid growth in sales in China, with projections of selling over 1 million units worth $12 billion this year. U.S. pressure on semiconductor exports continues, with possible further restrictions and control measures on AI model development.

Intel has presented the industry's first fully integrated optical compute interconnect (OCI) chiplet designed to significantly boost high-bandwidth data interconnect performance. Essential for growing AI demands, the milestone represents a step forward in silicon photonics, combining integrated circuits with lasers to enhance data transfer rates and support AI infrastructure scaling. The OCI chiplet aims to overcome the limitations of current electrical I/O interconnects by enabling higher bandwidth and longer-distance data transmission.

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Framework has partnered with DeepComputing, the company behind the very first RISC-V laptops, to build a RISC-V mainboard for the Framework Laptop 13. While the performance and features of these chips aren't on par with Intel or AMD (a Raspberry Pi 4 is likely faster), the integration is exciting as RISC-V is becoming more accessible. Framework hasn't announced a release date or price yet as the RISC-V mainboard is still in early development.