Tether Invests in Humanoid Robots. When Will They Be Launched

RBK-cryptoPublicado em 2025-12-09Última atualização em 2025-12-09

Resumo

Tether, the company behind the USDT stablecoin, has invested in humanoid robotics through a €70 million funding round in Generative Bionics, a spin-off from the Italian Institute of Technology (IIT). The startup is developing "physical AI" robots for industrial use and human interaction, leveraging two decades of IIT research. Tether stated these investments support technologies that "expand human potential and reduce reliance on centralized systems." The first industrial deployment programs for these robots are planned for early 2026, targeting manufacturing, logistics, healthcare, and retail sectors. A full concept of the humanoid robot will be unveiled at the CES exhibition in Las Vegas. Tether investment portfolio also includes AI, financial services, energy, and biotech.

Tether, the company behind the largest stablecoin USDT, has announced investments in the development of humanoid robots through the Italian Institute of Technology's (IIT) spin-off startup Generative Bionics. The funding round raised €70 million.

Generative Bionics specializes in creating robots with "physical AI" designed for industrial use and human interaction. The startup utilizes two decades of IIT's robotics research, holds exclusive licenses to key technologies, and employs about 70 engineers and AI specialists from the Italian Institute of Technology, according to the statement.

Tether describes these investments as supporting new technologies that "expand human potential and reduce dependence on centralized systems controlled by large tech companies." The company noted it has previously invested in similar developments: Tether funds the creation of neural interfaces through Blackrock Neurotech, and together with Northern Data and Rumble, is deploying a global network for AI utilization.

Generative Bionics states that the first industrial deployment programs for robots are planned for early 2026. They will cover industries such as manufacturing, logistics, healthcare, and retail. The first full-concept humanoid robot developed by the company will be presented at the CES international exhibition in Las Vegas (held annually in January).

Tether CEO Paolo Ardoino stated that the company "is proud to support a team that turns Italy's scientific leadership into global industrial influence." Both Ardoino and another Tether founder, Giancarlo Devasini, are originally from Italy.

Beyond AI investments, Tether's portfolio includes investments in financial services, energy, biotechnology, education, and media across various countries. The company holds stakes in projects spanning commodities, money transfers, sports, and entertainment.

Only 7 native tokens have remained in profit since the beginning of the year. And it's not Bitcoin

Binance suspended an employee for insider trading. What happened

Strategy purchased the largest batch of Bitcoin since July

Perguntas relacionadas

QWhat is the name of the startup that Tether invested in for humanoid robot development?

ATether invested in the startup called Generative Bionics, a spinoff of the Italian Institute of Technology (IIT).

QHow much funding was raised in the investment round for Generative Bionics?

AThe funding round raised €70 million.

QWhat is the primary purpose of the 'physical AI' robots being developed by Generative Bionics?

AThe 'physical AI' robots are designed for industrial use and human interaction.

QWhen are the first industrial deployment programs for these robots planned, and which sectors will they cover?

AThe first industrial deployment programs are planned for early 2026 and will cover manufacturing, logistics, healthcare, and commerce.

QWhere and when will the first full concept of the humanoid robot developed by Generative Bionics be presented?

AThe first full concept of the humanoid robot will be presented at the international CES exhibition in Las Vegas, which is held annually in January.

Leituras Relacionadas

Why the UXLINK hacker’s 14,336 ETH transfers raise fresh questions for DeFi

Recent on-chain activity reveals the UXLINK exploiter is actively laundering stolen funds, complicating tracing efforts. The September 2025 hack, which exploited a 'delegateCall' vulnerability to steal roughly $4.5 million, involved converting illicit assets into DAI and Ethereum. Recently, the attacker swapped over 10 million DAI for approximately 6,000.8 ETH and has deposited a total of 14,336.6 ETH into the privacy mixer Tornado Cash in recent weeks, including over $8.1 million worth in a single move. Simultaneously, wallets connected to the defunct Mining Express Ponzi scheme have been converting long-held assets, swapping 5,004 ETH for 8.8 million DAI. Following a separate exploit of the Jaredfromsubway.eth MEV bot, about $5.1 million was also routed to Tornado Cash. These incidents underscore a critical vulnerability in DeFi: while enabling permissionless transfers, the ecosystem lacks effective mechanisms to halt or manage illicit funds once in motion, allowing them to be moved and concealed relatively easily. This highlights the need for strengthened cross-network coordination and real-time threat detection to better safeguard the space.

ambcryptoHá 1h

Why the UXLINK hacker’s 14,336 ETH transfers raise fresh questions for DeFi

ambcryptoHá 1h

Li Fei-Fei's Latest Long-Form Article: When Video Generation, Robotics, and NVIDIA All Call Themselves World Models, We Need a Taxonomy

In a new article, Dr. Fei-Fei Li addresses the widespread and often inconsistent use of the term "world model" in AI. She proposes a clear, functional taxonomy rooted in the classic Partially Observable Markov Decision Process (POMDP) loop (agent → action → state → observation → agent). According to this framework, current systems called "world models" are different projections of this loop, categorized by their primary output: 1. **Renderers**: Output observations (pixels). Their goal is visual fidelity for human consumption (e.g., video generation models like Sora). They are the most commercially mature but are limited by a focus on appearance over physical accuracy. 2. **Simulators**: Output states (geometric, physical, dynamic representations). They provide a structurally accurate world for both human professionals (e.g., architects) and computational agents (e.g., robots for training). Li argues simulators are the crucial, underappreciated bridge, as they can underpin both rendering and planning. 3. **Planners**: Output actions. Given an observation and a goal, they decide what an agent should do next (e.g., robotic action models). This area is highly promising but remains the least mature for real-world deployment. Li highlights a key trend: the boundaries between these three categories are beginning to blur, as they all rely on a shared underlying understanding of geometry, physics, and dynamics. The logical endpoint is a unified world foundation model capable of switching between rendering, simulation, and planning based on downstream needs. This convergence, she concludes, is central to advancing spatial intelligence—enabling machines not just to talk about the world, but to truly understand, imagine, and interact with it.

marsbitHá 1h

Li Fei-Fei's Latest Long-Form Article: When Video Generation, Robotics, and NVIDIA All Call Themselves World Models, We Need a Taxonomy

marsbitHá 1h

Forbes Feature: Stablecoin Cross-Border Payments Are Faster, But Not Yet Cheaper

A Forbes feature delves into the state of stablecoin-based cross-border payments, noting rapid growth but a key shortfall: while faster and more accessible, they are not yet cheaper. At a recent industry conference in Mexico City, optimism about technology, regulation, and volume was tempered by discussions with practitioners. The core issue is liquidity. Traditional FX brokers charge 60-70 basis points, and stablecoins promise to slash this to 2-5 basis points. However, this theoretical cost advantage cannot be realized until deep liquidity pools are established at scale, requiring significant institutional capital inflow. A major adoption barrier is trust. Businesses often rely on long-standing relationships with traditional brokers, valuing reliability over marginal cost savings. This shift will be gradual. Furthermore, successful companies in the space are not positioning themselves as replacements for legacy systems like SWIFT, but as complements. They leverage stablecoins for speed while using traditional rails for their standardization and reliability in ensuring accurate payment details—a critical factor for supplier payments to avoid customs issues. Companies like Caliza, experiencing high monthly growth, exemplify this hybrid approach. The industry anticipates consolidation, as long-term viability will depend on securing the essential trifecta: proper licensing, robust fiat on/off-ramps, and deep liquidity. Without these, firms risk being mere intermediaries rather than building sustainable businesses.

marsbitHá 1h

Forbes Feature: Stablecoin Cross-Border Payments Are Faster, But Not Yet Cheaper

marsbitHá 1h

Forbes Feature: Cross-Border Payments with Stablecoins are Faster, But Not Yet Cheaper

A Forbes feature on stablecoin cross-border payments highlights rapid industry growth but notes the cost advantage remains theoretical. While stablecoins offer faster, 24/7, and more accessible international transfers compared to traditional forex brokers (charging 60-70 bps), they have not yet achieved their promised lower costs of 2-5 bps. The primary hurdle is a lack of deep, scaled liquidity pools, according to Imran Ahmad of Bitso Business. He states costs will only drop significantly with large-scale institutional and banking participation. Adoption faces a deeper challenge: trust. Businesses often stick with traditional brokers based on long-standing personal relationships, not just fees. Ezra Kebrab of cross-border payment firm Caliza emphasizes that reliability in handling complex details like tax codes is as critical as speed and cost. Contrary to some narratives, successful companies like Caliza see stablecoins as complementing, not replacing, existing infrastructure like SWIFT, which excels at payment standardization. Caliza itself uses SWIFT for many transactions and has seen monthly growth exceeding 40%. Ahmad predicts a future industry consolidation, where success will hinge on three pillars: proper licensing, reliable fiat on/off-ramps, and robust liquidity.

链捕手Há 1h

Forbes Feature: Cross-Border Payments with Stablecoins are Faster, But Not Yet Cheaper

链捕手Há 1h

Li Feifei's Latest Article: When Video Generation, Robotics, and NVIDIA All Claim to Have 'World Models,' We Need a Taxonomy

"World Model" has become a widely used yet ambiguous term in AI. Drawing from the classic POMDP framework (agent → action → state → observation), this article proposes a functional taxonomy to clarify the concept. It identifies three distinct types, categorized by their output in the perception-action loop: 1. **Renderers**: Output visual observations (pixels). These models, like advanced video generators, prioritize visual fidelity but often lack underlying physical accuracy. 2. **Simulators**: Output the state of the world (geometry, physics, dynamics). They provide a structurally accurate representation for professionals (e.g., architects) and serve as training environments for robots and AI agents. 3. **Planners**: Output actions. Given an observation and a goal, they determine what an agent should do next, closing the perception-action loop (e.g., vision-language-action models). While renderers are currently the most commercially mature and planners are the most aspirational, the article argues that **simulators are the crucial, underappreciated hub**. By working at the level of geometry and physics, a simulator can project upwards to create visuals for humans and downwards to predict action consequences for agents. The future lies in the convergence of these three functions. Emerging research and products, like World Labs' Marble model which outputs both visual splats and physical collision meshes, are beginning to blur these boundaries. The logical endpoint is a unified world foundation model capable of rendering, simulating, and planning based on a shared understanding of spatial and temporal structures—ultimately enabling machines to understand, imagine, and interact with the physical world.

链捕手Há 1h

Li Feifei's Latest Article: When Video Generation, Robotics, and NVIDIA All Claim to Have 'World Models,' We Need a Taxonomy

链捕手Há 1h

Trading

Spot
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow