A-Lab has revolutionized inorganic materials discovery

Combining ab-initio calculations, historical data from literature, and robotic testing, they're rapidly uncovering new compounds.

If you're excited to help Biotech using AI, keep this chart in mind - the best way to improve cost+time per drug is to reduce risk of trial failure, not to use AI to make a bunch of new molecules.

Alibaba cloud introduced Qwen-72B and Qwen-1.8B. Including Base, Chat and Quantized versions. Open source of course.

Qwen-72B has been trained on high-quality data consisting of 3T tokens, boasting a larger parameter scale and more training data to achieve a comprehensive performance upgrade. Additionally, researchers have expanded the context window length to 32K and enhanced the system prompt capability, allowing users to customize their own AI assistant with just a single prompt.

Qwen-1.8B striking a balance between maintaining essential functionalities and maximizing efficiency, generating 2K-length text content with just 3GB of GPU memory.

Huggingface here.

Paper here.

Wearable biosensor measures fertility hormones in sweat

Researchers have designed a wearable, ring-like biosensor for monitoring the hormone oestradiol in human sweat.

The technology is a fast-acting, non-invasive advance over conventional methods for tracking fertility and women’s health.

Whereas most biosensors use antibodies or enzymes to target proteins, Gao’s relies on aptamers — short bits of single-stranded DNA or RNA that are designed to fold such that they bind to targets ranging from small molecules to toxins. Although sometimes referred to as chemical antibodies, aptamers are much smaller than most antibodies and can be synthesized chemically, rather than in laboratory animals.

Researchers have previously designed aptamers to recognize cortisol, serotonin, caffeine and even some types of cancer.

To make the oestradiol sensor, the researchers designed two layers of material to work in tandem — an interface seeded with oestradiol-recognizing aptamers, and a gold-nanoparticle electrode covered in a material called MXene, which further enhances weak electrical signals. The aptamers are preloaded with single-stranded DNA that has been tagged with methylene blue, a dye that in this cases serves as an electrochemical probe.

#books This book will change how you look at biology. Truly outstanding treatment of the genetic and cellular world.

AI-generated human videos from pose detection is coming with Alibaba researcher's new 'Animate Anyone'.

OpenBCI launches a neuro-powered spatial computer

Galea Beta device includes a range of sensors that simultaneously measure the user’s heart, skin, muscles, eyes, and brain.

Galea Beta includes eye-tracking and displays from Finnish headset-maker, Varjo and can be ordered with the Varjo Aero, XR-3 or the recently announced XR-4.

The Galea Beta sensors can be used without the HMD, or can be tethered to a high-powered PC and used for collecting data from VR and XR environments.

Long-term goal for Galea is to bring everything you see on the table, together into one device. Optics, CPU, I/O and sensors, in one tightly synchronized integrated system.

According to a Chinese computer scientist who asked not to be named, the new Sunway is not the most powerful supercomputer in China at present.

But after details of it were given at the Supercomputing 2023 (SC23) conference in Denver, US, earlier this month, it gave the public some hints on how China has managed to sidestep US sanctions to build its own supercomputers.

This Chinese dark horse has also outdone leading supercomputers, including the Frontier, in computing efficiency.

It can maintain over 85 per cent of its peak performance in regular operation, ranking the highest among all heterogeneous systems – a type of common supercomputing architecture – and second among all systems.

Meanwhile, China’s most powerful supercomputer remains undisclosed and other supercomputing chips are also under development, according to the Chinese scientist who works at a top mainland university.

A very important sleep study came out

Sleep has a huge impact on someone's health and even health span, but now it seems that "sleep regularity is an important predictor of mortality risk and is a stronger predictor than sleep duration."

Thus sleep regularity should be a simple, yet effective target for improving general health and survival.

Google has quietly delayed the public debut of Gemini to January

Sundar Pichai recently decided to scrap a series of Gemini events, originally scheduled this week after the company found the AI didn’t reliably handle some non-English queries.

It’s rare for Google to launch a major product between Thanksgiving and the end of the year, but Google intended to make an exception for Gemini because it’s arguably the company’s most important initiative in a decade.

The Gemini event in Washington was intended to showcase the technology to policymakers and politicians, which have increasingly discussed potential regulations involving AI.

No GPU but wanna create your own LLM on laptop?

Here is a QLoRA on CPU, making LLM fine-tuning on client CPU possible.

Code.

Taiwan's National Science and Technology Council has published a list of key technologies that are significant to Taiwan's national security: semiconductor manufacturing process technology under 14 nm included.

Can computers simulate brains?

Scientists have been exploring the intersection of math, computers, and neuroscience for decades. Today, machine learning is unlocking new possibilities in brain modeling.

Fascinating Nature paper on the latest in the field.

Apple released new software from machine learning research.

MLX is an efficient machine learning framework specifically designed for Apple silicon (i.e. your laptop!)

Code.

This may be Apple's biggest move on open-source AI so far: MLX, a PyTorch-style NN framework optimized for Apple Silicon, e.g. laptops with M-series chips.

The release did an excellent job on designing an API familiar to the deep learning audience, and showing minimalistic examples on OSS models that most people care about: Llama, LoRA, Stable Diffusion, and Whisper.