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Users cry foul after AMD stripped memory crypto from its consumer CPUs

A decade ago, AMD added a protection to its high-end CPUs to protect them against cold boot attacks and other types of physical exploits that siphon sensitive data out of the connected memory chips. Short for Transparent Secure Memory Encryption, TSME encrypts the entire contents stored in memory, making the data useless to physical attackers.

Over time, AMD added TSME to lower-end processors, including the consumer version of its Ryzen chips, a CPU that costs less than the Pro version. Over the years, users of these lower-end chips have gotten used to the added security. Recently and without warning or notice, this lower-end line of AMD chips suddenly dropped the protection, and did so in a way that was impossible to detect on Windows machines and required a fair amount of technical work when using Linux.

Now you see it, now you don't

AMD has yet to say why TSME worked on these CPUs, or even to confirm the change. AMD declined to answer questions sent by email other than to say TSME "is a security feature only applied to PRO CPUs as part of AMD PRO Technologies." The statement is the first known time the chipmaker has explicitly made this restriction public.

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Β© Andrew Cunningham

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Intel stakes new claim in physical AI with robotics chips

Intel is invading the physical AI space with a reentry into the robotics market it quit many years ago amid financial struggles.

The robotics strategy is part of the company’s larger plan to establish AI on the β€œedge,” in which devices have the computing capability to run AI locally. Many devices lack AI capabilities and have to offload processing to the cloud.

The chipmaker said its Intel Series 3 processors are now in 130 edge AI and robotics designs. It also had a design win with SensoryAI, which provides technology for robots that include Ella, a robotic barista made by Crown Digital.

The company’s Core Ultra Series 3 processors are derivatives of chip designs intended for laptops. But Intel has achieved a level of power efficiency for long battery life that allows those chips to be adapted for handheld devices and laptops.

Intel also said it can build advanced robotics chips thanks to its latest manufacturing technologies.

For example, many robotic functions, such as computer vision and real-time controls, can be integrated into a single chip. Previously, functions like graphics and movement and control were distributed among different cores in a chip.

SensoryAI, for example, has a chip architecture that provides the robotic barista β€” which is more like a robotic arm β€” with AI capabilities, Intel said.

The main β€œAvatar” agent handles customers as the main β€œElla” agent reasons and executes the task. If Ella encounters errors, it passes on the issue to a Guardian agent, which helps with the recovery. Some issues could include making sense of an order, or cups that might be stuck.Β 

The three agents are embedded in a single piece of Core Ultra Series 3 silicon.

Intel is displaying some of those robots at the Computex trade show in Taiwan. The company shared a video of a humanoid-style robot from the floor in a X.com post Β 

This is not Intel’s first attempt at the robotics market. Intel sold robotics chips and kits when it was a dominant chip player in the field, but curtailed efforts in 2021 after Pat Gelsinger took over as CEO and restructured the company to focus on manufacturing.

Robotics is now back on the menu under new Intel CEO Lip-Bu Tan, who replaced Gelsinger last year. He has restructured to company to focus on high-growth areas that can generate high returns.

A Morgan Stanley study last year indicated the robotics market could be worth $5 trillion by 2050 β€” and more than 1 billion humanoid robots could be in operation.Β 

Robots are seen to improve human productivity and manufacturing output. For example, they could help factories that are facing labor shortages or be used to complete tasks that are dangerous.Β 

However, challenges remain. There isn’t yet enough real-world data to train robots to do targeted work. And the AI models β€” generally called world models β€” they will need are still under development.Β 

Training robots to do a specific job requires a sequence of events to happen in succession without any errors. Companies are still training robots to spot and understand errors, analyze possible resolutions, and take the right corrective action.

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