Lifeboat Foundation

It seems Intel is set to retake the PC performance crown convincingly with its 12 generation Alder Lake processors, even in the affordable price segment.

A leaked sample of the Core i3-1200 version of the processor has been benchmarked by Chinese hardware site XFASTEST and it crushes the competition in the price segment.

When compared to AMD Zen 2-based Ryzen 3 3300X and 3,100 DIY CPUs, the Intel Core i3-1200 processor paired with the ASRock Z690 Steel Legend WiFi 6E DDR4 motherboard outperformed the AMD processors in most benchmarks as can be seen below:

At its re: Invent 2021 conference today, Amazon announced Graviton3, the next generation of its custom ARM-based chip for AI inferencing applications. Soon to be available in Amazon Web Services (AWS) C7g instances, the company says that the processors are optimized for workloads including high-performance compute, batch processing, media encoding, scientific modeling, ad serving, and distributed analytics.

Alongside Graviton3, Amazon unveiled Trn1, a new instance for training deep learning models in the cloud — including models for apps like image recognition, natural language processing, fraud detection, and forecasting. It’s powered by Trainium, an Amazon-designed chip that the company last year claimed would offer the most teraflops of any machine learning instance in the cloud. (A teraflop translates to a chip being able to process 1 trillion calculations per second.)

As companies face pandemic headwinds including worker shortages and supply chain disruptions, they’re increasingly turning to AI for efficiency gains. According to a recent Algorithmia survey, 50% of enterprises plan to spend more on AI and machine learning in 2021, with 20% saying they will be “significantly” increasing their budgets for AI and ML. AI adoption is, in turn, driving cloud growth — a trend of which Amazon is acutely aware, hence the continued investments in technologies like Graviton3 and Trn1.

The electronics were also improved with a new full-color touchscreen interface and a modular wiring system. An RGB LED lighting system adds nice ambiance and could help users create more exciting time lapse videos of their prints. Prusa is even considering releasing an official, though unsupported, Klipper firmware for those users who have grown to love Klipper in other CoreXY printers.

The most exciting feature by far, however, is the new swappable toolhead system. This is similar to the E3D ToolChanger design and lets the printer switch between different extruders during a print, allowing for multicolor or multi-material prints. An innovative calibration routine ensures that quality doesn’t suffer after a tool change.

Prusa Research hasn’t yet announced an official release date, but you can reserve a pre-order by placing a $200 deposit right now. A semi-assembled Prusa XL with a single toolhead will cost $1,999. A Prusa XL with dual toolheads will cost $2,499 and a Prusa XL with five toolheads will cost $3,499.

According to a new report from Korea, Samsung is considering adding water resistance to its cheaper devices, starting with the Galaxy A33.

Hackers have been increasingly using RTF Template Injection method in widespread phishing attacks.

22-year-old hacker, sixth member of an international hacking group called “The Community,” has been jailed for stealing millions in cryptocurrency.

The lower-end Snapdragon 7c+ Gen 3 offers a more modest 60% jump in multi-core CPU performance, and 30% in single-core workloads. The GPU gets a meaningful 70% boost as well.

Qualcomm says the 8cx Gen 3 is manufactured on the 5nm process node, which suggests that it uses Arm’s Cortex-X1 cores or a modified Kryo 680 design — not the newer Arm Cortex-X2. In that respect, it seems similar to the Snapdragon 888, its previous flagship mobile SoCs. Still, the decision to move away from 7nm should mean better performance per watt. But just how powerful is this new high-end chip?

Continue reading “Qualcomm’s new PC chips are good, but they still can’t match Apple’s M1” »

For the first time, computer scientists and mathematicians have used artificial intelligence to help prove or suggest new mathematical theorems in the complex fields of knot theory and representation theory.

The astonishing results have been published today in the pre-eminent scientific journal, Nature.

Professor Geordie Williamson is Director of the University of Sydney Mathematical Research Institute and one of the world’s foremost mathematicians. As a co-author of the paper, he applied the power of Deep Mind’s AI processes to explore conjectures in his field of speciality, representation theory.

ISM001-055 demonstrated highly promising results in multiple preclinical studies including in vitro biological studies, pharmacokinetic and safety studies. The compound significantly improved myofibroblast activation which contributes to the development of fibrosis. ISM001-055’s novel target is potentially relevant to a broad range of fibrotic indications.

“We are very pleased to see Insilico Medicine’s first antifibrotic drug candidate entering into the clinic,” said Feng Ren 0, PhD, CSO of Insilico Medicine. “We believe this is a significant milestone in the history of AI-powered drug discovery because to our knowledge the drug candidate is the first ever AI-discovered novel molecule based on an AI-discovered novel target. We have leveraged our end-to-end AI-powered drug discovery platform, including the usage of generative biology and generative chemistry, to discover novel biological targets and generate novel molecules with drug-like properties. ISM001-055 is the first such compound to enter the clinic, and we expect more to come in the near future [1].”

Previously, Insilico Medicine demonstrated its ability to generate drug-like hit molecules using AI with the publication of the Generative Tensorial Reinforcement Learning (GENTRL) system for a well-known target in record time [2]. It also demonstrated the target’s proof of concept by applying deep learning techniques for the identification of novel biological targets. This novel antifibrotic program combined these target discovery and generative chemistry capabilities. Notably, Insilico Medicine completed the entire discovery process from target discovery to preclinical candidate nomination within 18 months on a budget of $2.6 million.