First-of-its-kind, data-driven machine learning model reveals in fine detail the pathway that solid-state reactions take.
Category: robotics/AI – Page 16
AI redesign helps enzymes evolve beyond natural limits
Researchers showed that AI-redesigned botulinum neurotoxin proteases provided more stable starting points for directed evolution, allowing enzymes to access beneficial mutations that were poorly tolerated in wild-type backgrounds. In BoNT/E models, the approach improved activity, evolvability, and specificity, including an ataxin-2-targeting variant with markedly reduced cleavage of the native SNAP25 substrate.
Noninvasive AI-based system translates brain signals into written text
Some physical injuries and neurological conditions can temporarily or permanently impair movement, leaving some people unable to speak, type on keyboards or use electronic devices. Brain-computer interfaces (BCIs), systems that can decode brain activity patterns and convert them into computer commands or written text, could be of great value for paralyzed patients.
Despite their potential, most of the best-performing BCIs developed to date require patients to undergo invasive surgical procedures. These systems typically rely on small sensors that need to be implanted on or within the brain and can detect electrical signals associated with neural activity.
Researchers at Meta artificial intelligence (AI), Université PSL and Hospital Foundation Adolphe de Rothschild recently introduced a noninvasive brain activity-to-text approach that does not require surgical procedures. Their proposed approach, presented in Nature Neuroscience, combines a new deep learning algorithm with electroencephalography (EEG) or magnetoencephalography (MEG) recordings.
New Pass-ta-key attacks let malware hijack Google-synced passkeys
Security researchers have discovered three attacks that allow malware on already-compromised Windows devices to abuse Google Password Manager’s synced passkeys to take over accounts, bypass user verification, and extract passkey private keys.
Passkeys are a passwordless authentication method that uses cryptographic keys stored on a user’s device to sign in to online accounts.
They are considered safer than passwords because they cannot be guessed, reused, or easily stolen through phishing, while also allowing users to authenticate with a PIN or biometrics, such as a fingerprint or facial recognition.
New Generation Of Intelligent Drones Defined By Technology Convergence
One of the most fascinating instances of current technological convergence is the quick development of unmanned aerial systems (UAS), also referred to as drones. A sophisticated ecosystem of intelligent autonomous platforms that can support defense, homeland security, critical infrastructure, emergency response, agriculture, logistics, energy, healthcare, and environmental protection is rapidly emerging from what started out as remotely piloted aircraft for military reconnaissance and commercial photography.
It is increasingly evident in our new digital era that the most significant technological advancements seldom come from a single invention; rather, they emerge when several technologies develop concurrently and start to support each other. This is called technology convergence, and it is true with trends in drones.
According to Grandview Research The global drone market size was valued at USD 83.8 billion in 2025 and is projected to grow from USD 96.4 billion in 2026 to USD 182.4 billion by 2033. Those are impactful statistics.
How AI helps scientists design the next generation of medicines
Ultimately, Sapra says, the end-state vision for AI in biologic drug discovery is what the field calls “de novo” design. For this, the goal is for AI to generate entirely new protein sequences that precisely fit the desired drug properties. This includes designing the structure, predicting safety, how it will behave in the body and how to make it manufacturable.
“The field is making great progress toward a completely AI-generated biologic, designed from scratch all the way to a clinical candidate,” Sapra says. “As we continue to leverage frontier models and fine-tune them with the right datasets, we bring ourselves closer to this reality. I believe it will come. It’s a matter of time.”
Several key elements are needed to reach this point, however. First is richer and more standardized training data across the industry. Second, robust evaluation benchmarks for AI-generated candidates. And third, teams that know how to work at the intersection of machine learning and biology. Of all the prerequisites, however, safety prediction may be the most consequential, and perhaps the least discussed, Sapra says.