Category: Biometrics
Neurotechnology spinoff SkyBiometry launches AI infrastructure suite
SkyBiometry, a subsidiary of biometric technology company Neurotechnology, has announced the launch of an AI factory and an infrastructure suite of products, offering AI-ready hardware infrastructure, private AI clouds, and orchestration and deployment of AI models.
The products are intended to support organizations building large language models (LLMs), generative AI applications and computer vision systems and draw on Neurotechnology’s background in high-performance computing.
The move comes as the EU prepares to propose the EU Cloud and AI Development Act (CADA), which aims to strengthen Europe’s cloud computing and AI capabilities. SkyBiometry sees its task as removing infrastructure bottlenecks that hinder innovation through specialized, high-performance environments, according to the firm’s CEO, Mantas Kundrotas.
The company has already deployed its products across several industries, including legal services, for which it has built custom LLM models and vector search tools used in biometrics and other applications. In healthcare, SkyBiometry implemented on-premises automation for patient scheduling that keeps medical data on-site, while for telecommunications clients, it has developed automated voice call analysis with keyword-based filtering.
“By providing end-to-end services, from initial hardware design to the operation of secure private clouds and the delivery of fully production-ready systems, we enable our clients to focus on their core AI development while we handle the complexity of the underlying technology stack,” says Kundrotas.
On the hardware side, the company says its infrastructure uses current-generation GPUs and low-latency networking. Its private cloud service offers bare-metal hosting with dedicated compute and data sovereignty, while AI models can be deployed through managed Kubernetes and NVMe storage.
Lithuania-based Neurotechnology develops algorithms and software based on deep neural networks for various applications, including biometric identification, natural language processing (NLP), computer vision and others. It launched SkyBiometry as a spin-off in 2012 with the goal to provide biometric technology as a service, offering its own cloud-based facial recognition API.
The company later developed a purpose-built AI stack that solves the GPU idle time problem caused by data bottlenecks. The case study demonstrates how the AI Factory cluster, a high-performance computing environment designed specifically for AI development, was tested.
YouTube offers its biometric deepfake detection tool to celebrities
After content creators, politicians and journalists, YouTube will also enable celebrities to access its likeness detection tool, allowing them to remove deepfakes and stop unauthorized impersonation on the platform.
YouTube’s biometric likeness technology scans for AI-generated videos that match a verified user’s appearance. The feature functions similarly to Content ID, a tool that helps detect and remove copyrighted material on the platform, according to a company blog post.
Users can verify their identity by submitting a government ID and a self-recorded video for face biometrics matching. Those enrolled in the program receive alerts when potential matches surface and can request removal if the content goes against YouTube’s privacy policy.
The feature was first offered to creators in the YouTube Partner Program last year, while in March it was expanded to government officials, journalists and political candidates. Expansion to other famous people is the next logical step.
YouTube says it has collaborated with talent agencies and management companies, such as CAA, UTA, WME, and Untitled Management, to provide the tech to entertainers.
While some celebrities have recoiled at the thought of seeing their deepfakes online, others are seeing it as a money-making tool. Talent agency CAA has, for instance, built a database with AI developer Veritone that stores their clients’ digital likenesses and voices to give them control and compensation in cases of AI use.
YouTube is not the only company that is introducing measures to protect famous people from unauthorized deepfakes, as AI-generated videos fuel scams, political misinformation and reputational manipulation.
Last year, OpenAI committed to “strengthen guardrails around replication of voice and likeness when individuals do not opt-in,” following Breaking Bad star Bryan Cranston’s decision to reach out to the actors’ union SAG-AFTRA over unauthorized AI-generated versions of his likeness.
Meanwhile, both OpenAI and YouTube have voiced support for the proposed NO FAKES Act, a U.S. federal law designed to protect individuals’ voices and visual likenesses from unauthorized, AI-generated digital replicas.
Greece exempts Britons from EES biometric registration for summer
Alarm at severe delays caused by the EES rollout in European airports may have dampened British enthusiasm for the traditional summer getaway, but Athens is looking to get Britons back on board.
Greece has just announced biometric exemptions for British visitors. This means they will not be required to provide fingerprint and face biometrics. In 2025 nearly five million Brits headed to the Mediterranean country, representing a huge contributor to Greece’s tourism industry.
Eleni Skarvedi, director of the Greek National Tourism Organization in the UK, told The Independent that the move is intended to ensure a “smoother and more efficient travel experience in Greece.”
“Practically, this means that the entry process in place before the implementation of the EES will remain unchanged,” she said to the newspaper.
This means Britons will need to have their passports manually checked and stamped while personal data is “skimmed” and logged. EES kiosks at Athens airport will remain open to other third-country nationals, but won’t be open to British travelers.
The Greek embassy in London made it clear that British passport holders are excluded from biometric registration at all Greek border crossing points. However, Brussels has taken a somewhat dim view of Athen’s decision.
A spokesperson for the European Commission said contact has been made with Greek authorities to “receive clarifications” and that the legal framework underpinning EES “does not foresee blanket exemption” for specific third-country nationals and for an extended duration.
Generally, however, the EES does allow flexibility for the registration of biometrics with suspension of collection possible at specific borders and for a limited duration in cases of “exceptional circumstances that lead to excessive waiting times,” the spokesperson said, quoted in The Independent.
The decision by Greece to suspend the EES system across its border checkpoints just for British visitors and for the whole of summer may cause tension with the EU. Brussels’ concern may grow if other countries that are popular destinations for Britons, such as Spain and Portugal, decide to follow suit. While there is no indication of that just yet, France has already bent the rules by allowing visitors in cars to forgo EES at French checkpoints at the Port of Dover in southeast England.
The first week of Europe’s EES was marred by delays even as there was widespread suspension of the biometrics enrollment that forms the foundation of the system. Airports and airlines called for more flexible implementation rules in response, but appeared in some cases to have botched staffing and organization.
Advancements in voice AI come with widespread risk to biometrics
Deepfake voices are already a challenge for authentication systems. But the task is getting tougher, as big players pursue voice AI products that could turn speech into a scalable attack surface for identity systems, creating a world in which synthetic speech represents a real identity infrastructure risk.
The latest to join the likes of ElevenLabs and OpenAI in offering APIs for voice biometrics is xAI – the same firm that gave the world Grok the Deepfake Nude Machine. Marktechpost reports that the company has launched standalone Speech-to-Text (STT) and Text-to-Speech (TTS) APIs, “both built on the same infrastructure that powers Grok Voice on mobile apps, Tesla vehicles, and Starlink customer support.”
The market for speech APIs is getting busier. Rapid advances in voice AI are lowering costs and skill barriers for voice cloning, and companies such as Deepgram and AssemblyAI already have established user bases. Others will follow xAI into the market.
The cumulative result is an undermining of trust in voice as an authentication factor – and a need to rethink speaker biometrics in the context of agentic identity.
Grok, say ‘I need help’ in the voice of Morgan Freeman
Grok’s APIs will make it even easier for millions of people to create believable synthetic voices. For text-to-speech, which converts written text into spoken audio, the API “delivers fast, natural speech synthesis with detailed control via speech tags, and is priced at $4.20 per 1 million characters.” It supports 20 languages and five distinct voices, and offers the ability to manipulate delivery with speech tags.
Grok’s record on nefarious use speaks for itself. What are the chances the same user base that flooded X with fake nudes will see the potential for fraud and mischief in the AI’s TTS API? It is a rhetorical question, but it has real-world implications for voice as a reliable biometric modality for identity infrastructure.
In recent weeks, ElevenLabs launched a system to enable companies to deploy AI agents. According to USA Today, the tool “allows teams to convert internal documentation and workflows into conversational agents, without the need for extensive technical development.”
“These agents are designed to follow structured processes, but deliver responses that sound natural within context.”
This month, Microsoft also launched three new foundational AI models, including a voice generation engine, MAI-Voice-1.
Consider how many phone calls already come from bots. Now consider how easily one might use AI to clone the voice of your loved one. The threshold for certainty is disappearing, at least without rigorous voice liveness and continuous monitoring. The question stands to become, is voice worth the risk?
Be careful whose voice offers an answer.
Voice AI expands attack surface for speaker biometrics as APIs proliferate
Deepfake voices are already a challenge for authentication systems. But the task is getting tougher, as big players pursue voice AI products that could turn speech into a scalable attack surface for identity systems, creating a world in which synthetic speech represents a real identity infrastructure risk.
The latest to join the likes of ElevenLabs and OpenAI in offering APIs for voice biometrics is xAI – the same firm that gave the world Grok the Deepfake Nude Machine. The company has launched standalone Speech-to-Text (STT) and Text-to-Speech (TTS) APIs, “both built on the same infrastructure that powers Grok Voice on mobile apps, Tesla vehicles, and Starlink customer support.”
The market for speech APIs is getting busier. Rapid advances in voice AI are lowering costs and skill barriers for voice cloning, and companies such as Deepgram and AssemblyAI already have established user bases. Others will follow xAI into the market.
The cumulative result is an undermining of trust in voice as an authentication factor – and a need to rethink speaker biometrics in the context of agentic identity.
Grok, say ‘I need help’ in the voice of Morgan Freeman
Grok’s APIs will make it even easier for millions of people to create believable synthetic voices. For text-to-speech, which converts written text into spoken audio, the API “delivers fast, natural speech synthesis with detailed control via speech tags, and is priced at $4.20 per 1 million characters.” It supports 20 languages and five distinct voices, and offers the ability to manipulate delivery with speech tags.
Grok’s record on nefarious use speaks for itself. What are the chances the same user base that flooded X with fake nudes will see the potential for fraud and mischief in the AI’s TTS API? It is a rhetorical question, but it has real-world implications for voice as a reliable biometric modality for identity infrastructure.
In recent weeks, ElevenLabs launched a system to enable companies to deploy AI agents. According to USA Today, the tool “allows teams to convert internal documentation and workflows into conversational agents, without the need for extensive technical development.”
“These agents are designed to follow structured processes, but deliver responses that sound natural within context.”
This month, Microsoft also launched three new foundational AI models, including a voice generation engine, MAI-Voice-1.
Consider how many phone calls already come from bots. Now consider how easily one might use AI to clone the voice of your loved one. The threshold for certainty is disappearing, at least without rigorous voice liveness and continuous monitoring. The question stands to become, is voice worth the risk?
Be careful whose voice offers an answer.
Voice morphing attack blends identities to bypass voice biometrics: study
A new research paper explores a signal-level approach to voice morphing attacks that exposes vulnerabilities in biometric voice recognition systems.
The abstract describes Time-domain Voice Identity Morphing (TD-VIM) as “a novel approach for voice-based biometric morphing” which “enables the blending of voice characteristics from two distinct identities at the signal level.” TD-VIM allows for seamless voice morphing directly in the time domain, allowing “identity blending without any embeddings from the backbone, or reference text.”
“In biometric systems, it is a common practice to associate each sample or template with a specific individual,” the authors say. Advanced Voice Identity Morphing (VIM) enables the generation of a sample that blends the identities of two or more speakers. “The morphed voice sample can be used to match all identities whose voice samples are employed to generate morphing attacks, thus posing a high risk to application scenarios, such as banking and finance, where single identity verification is essential.”
To explore the problem, the research team “created four distinct morphed signals based on morphing factors and evaluated their effectiveness using a comprehensive vulnerability analysis.” Data was benchmarked against the Generalized Morphing Attack Potential (G-MAP) metric, “measuring attack success across two deep-learning-based Speaker Verification Systems (SVS) and one commercial system, Verispeak.”
“Our targeted analysis on Verispeak highlights TD-VIM’s success rate in challenging advanced SVS defenses,” says the conclusion. “The findings underscore TD-VIM’s potential to bypass sophisticated verification measures, emphasizing the importance of enhancing SVS security.”
The research comes out of the Indian Institute of Technology and the Norwegian University of Science and Technology (NTNU).
