Quantum Computing

The Next Big Quantum Computer Has Arrived

Quantinuum unveiled Helios, a quantum computer with 98 physical qubits and 48 logical error-corrected qubits, a 2:1 ratio. Helios introduces Guppy, a new programming language designed to enable algorithms to scale from Helios to future, larger machines. JPMorgan Chase is an early customer using Helios to run complex algorithms for business problems.

This 2:1 ratio is unique and impressive, said Prineha Narang, professor of physical sciences and electrical and computer engineering at UCLA, and partner at venture-capital firm DCVC. Other companies require anything from dozens to hundreds of physical qubits to create one logical qubit. But maximizing the number of error-corrected logical qubits is complex and typically involves trade-offs in other areas of performance, Narang said.

Robotics

Robotics and Physical AI: Intelligence in Motion

Globally, the market for both traditional and AI-enabled robots in industrial and service applications is projected to top $392 billion by 2033, the total addressable global market for humanoids is expected to reach $38 billion by 2035.

The Physical AI 6Ps Framework for understanding the robotics and physical AI market revolves around six key market capabilities, some led by people, others by machines, and still others co-led by both people and machines.

AI

Inside Microsoft’s New AI ‘Super Factory’

Microsoft is doubling its data center footprint over the next two years, including building a new AI “super factory” in Atlanta. The complex spans more than 1 million square feet across 85 acres. The company is investing over $34 billion in capital expenditures. These facilities feature two-story construction for better networking and reduced latency.

Microsoft’s Fairwater network will host hundreds of thousands of Nvidia GPUs to serve customers like OpenAI, Mistral AI, and xAI. A novel liquid-cooling system enables GPUs to be placed closely together, improving efficiency.

Autonomous Driving

Waymo is hitting the highway — but can it handle the speed?

Waymo is finally ready to hit the highway. Starting today, the company’s robotaxis will gradually start to include more highway trips in its routes in Phoenix, San Francisco, and Los Angeles. In addition, Waymo’s Bay Area service is extending south to San Jose, including 24/7 curbside access at both terminals of San Jose International Airport — the company’s second airport service after Phoenix.

The challenges of highway driving are numerous. Higher traffic speeds mean Waymo’s autonomous vehicles will have less time to make consequential decisions. Any mistake can carry a higher degree of severity. The company’s engineers say that their hardware stack, which include lidar, camera, and radar, have 360-degree visibility and can “see” objects up to three football fields away.

NVIDIA pushes into robotaxi space with major Uber partnership

US chipmaker NVIDIA has unveiled a strategic move designed to accelerate commercial-scale autonomous mobility worldwide: it will team up with ride hailing service Uber to build a global Level 4 (L4) robotaxi and autonomous-delivery fleet network, starting in 2027 and targeting about 100,000 vehicles.

At the heart of the initiative is NVIDIA’s Drive AGX Hyperion 10 reference architecture: a modular compute/sensor platform designed to help automakers and fleet operators deploy L4-ready vehicles at scale, the company states in a press release.

Automakers such as Stellantis, Lucid and Mercedes-Benz are already listed as collaborators building autonomous passenger vehicles on the Hyperion 10 platform. Uber will integrate human drivers and autonomous vehicles into a single ride-hailing network powered by the Hyperion platform and a shared AI “data factory” built with NVIDIA’s Cosmos foundation technology.

Healthcare

These technologies could help put a stop to animal testing

Earlier this week, the UK’s science minister announced an ambitious plan: to phase out animal testing.Testing potential skin irritants on animals will be stopped by the end of next year. Advanced in organs on chips, digital twins, and AI are ushering in a new era of research and drug development.

Take “organs on chips,” for example. Researchers have been creating miniature versions of human organs inside tiny plastic cases. These systems are designed to contain the same mix of cells you’d find in a full-grown organ and receive a supply of nutrients that keeps them alive.

Today, multiple teams have created models of livers, intestines, hearts, kidneys and even the brain. And they are already being used in research. Heart chips have been sent into space to observe how they respond to low gravity. The FDA used lung chips to assess covid-19 vaccines. Gut chips are being used to study the effects of radiation.

The computers that run on human brain cells

Some researchers are trying to replicate the super-efficient structure of the brain using silicon chips. This approach, broadly called neuromorphic computing, takes inspiration from how neurons connect and fire to communicate. Specifically, some systems seek to mimic how neurons must charge to a threshold before firing an electrical impulse.

Biocomputing, on the other hand, goes back to the biological source material. Starting with induced pluripotent stem (iPS) cells, which can be reprogrammed to become almost any type of cell, researchers culture communities of brain cells and nurture them with nutrients and growth factors. To communicate with them, researchers sit the cells on electrode arrays, then pass signals and commands to them as sequences of electrical pulses. These signals change the way that ions flow into and out of neurons, and might prompt some cells to fire an electrical impulse known as an action potential. The biocomputer electrodes can detect these signals and employ algorithms to convert them to usable information.

The most common biocomputing approach cultures the neurons as 3D clusters called organoids. The composition of these brain-cell communities varies, depending on how the iPS cells differentiate, but typically includes neurons and cells that support them, such as astrocytes and oligodendrocytes.