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22 Jan 2026, 13:01
GoMining, Jacob & Co. Debut $40K Luxury Bitcoin Watch Paired With 'Digital Miner'
Looking for a flashy new timepiece? GoMining's collab with Jacob & Co. pairs a Bitcoin-themed luxury watch with a share of mining profits.
22 Jan 2026, 12:55
On-Device AI Surge: Quadric’s Strategic Pivot from Cloud to Edge Inference Pays Off Spectacularly
BitcoinWorld On-Device AI Surge: Quadric’s Strategic Pivot from Cloud to Edge Inference Pays Off Spectacularly San Francisco, March 2025 – A profound architectural shift is reshaping the artificial intelligence landscape, moving critical processing from centralized cloud data centers to the devices in our hands, cars, and offices. Consequently, this transition is creating significant winners, with chip-IP startup Quadric emerging as a notable beneficiary. The company’s strategic focus on powering on-device AI inference is now delivering substantial financial returns, evidenced by a projected licensing revenue surge to between $15 million and $20 million for 2025. Quadric Capitalizes on the On-Device AI Inference Revolution The era of sending every AI query to a distant cloud server is rapidly evolving. Companies and governments globally are now aggressively pursuing tools for local AI execution. This strategic move aims to dramatically reduce cloud infrastructure costs and build sovereign technological capability. Quadric, founded by veterans of the early bitcoin mining firm 21E6, is positioning its technology at the heart of this shift. The startup licenses programmable AI processor intellectual property (IP), essentially providing a blueprint that customers embed into their own silicon designs. CEO Veerbhan Kheterpal explained the core market dynamic in an exclusive interview. “The widespread adoption of transformer-based models in 2023 pushed inference into ‘everything,'” he stated. This created a sharp business inflection over the past 18 months. More enterprises now seek to run AI locally rather than rely entirely on cloud-based services. For instance, real-time functions in automotive driver assistance systems cannot tolerate latency. Therefore, on-device processing becomes not just economical but essential. The Financial and Strategic Payoff Quadric’s financial trajectory underscores the market’s validation. The company’s licensing revenue is expected to leap from approximately $4 million in 2024 to between $15 million and $20 million in 2025. Furthermore, it is targeting up to $35 million this year as it builds a royalty-driven business model. This growth has significantly buoyed the company’s valuation. Its post-money valuation now sits between $270 million and $300 million, a substantial increase from around $100 million during its 2022 Series B funding round. Investors are clearly taking note of this momentum. Quadric recently announced a $30 million Series C funding round led by the ACCELERATE Fund, managed by BEENEXT Capital Management. This investment brings its total funding to $72 million. Kheterpal connected this investor interest directly to the broader industry trend. “The raise comes as investors and chipmakers look for ways to push more AI workloads from centralized cloud infrastructure onto devices and local servers,” he told Bitcoin World. Expanding from Automotive into a Broader Ecosystem Quadric’s journey began in the automotive sector, a natural early adopter for on-device AI. Here, low-latency inference powers critical real-time functions like advanced driver-assistance systems (ADAS). However, the company’s vision and market have expanded decisively. Today, its technology targets a diverse portfolio including AI-powered laptops, industrial devices, and printers. The startup’s customer base now spans major industry players. It includes Kyocera and Japan’s automotive supplier Denso, which builds chips for Toyota vehicles. Kheterpal confirmed that the first commercial products based on Quadric’s IP are slated to ship this year, beginning with laptops. This expansion represents a deliberate scaling strategy. The company is moving from a niche automotive focus to addressing the ubiquitous demand for edge AI processing. Key Advantages of Quadric’s Approach: Programmability: Unlike fixed-function AI accelerators, Quadric’s IP is programmable. This allows customers to support new AI models through software updates instead of costly hardware redesigns. Chip-Agnostic Design: The technology is not tied to a specific silicon process. Customers can integrate the IP into their preferred manufacturing node. Full Stack Solution: Quadric provides not just the processor blueprint but also a complete software stack and toolchain to run models for vision, voice, and other tasks on-device. The Rising Tide of Sovereign AI Strategies Beyond commercial applications, a powerful geopolitical and economic driver is fueling Quadric’s growth: the global push for sovereign AI. Nations are increasingly seeking to reduce their strategic dependence on U.S.-based cloud infrastructure for critical AI capabilities. This involves building domestic expertise across the compute, model, and data spectrum. Kheterpal noted that Quadric is actively exploring opportunities in markets like India and Malaysia, where this sentiment is particularly strong. The company counts Moglix CEO Rahul Garg as a strategic investor, specifically to help shape its “sovereign” approach for the Indian market. This strategic direction aligns with analysis from major consulting firms. For example, EY highlighted in a November 2024 report that the sovereign AI approach has gained significant traction. Policymakers and industry groups are now pushing for domestic AI capabilities rather than relying entirely on foreign infrastructure. Navigating the Hardware vs. Software Evolution Challenge A central challenge in the AI semiconductor industry is the mismatch between development cycles. AI model architectures, like the shift from convolutional neural networks (CNNs) to transformers, can evolve in months. In contrast, designing and manufacturing a new chip typically requires multiple years. Kheterpal identified this disparity as a critical pain point for customers. They need processor IP that can keep pace through software updates, avoiding expensive and time-consuming silicon redesigns with every architectural shift. Quadric positions its programmable solution as a direct answer to this problem. “We were looking to build a similar CUDA-like or programmable infrastructure for on-device AI,” Kheterpal said, drawing a parallel to Nvidia’s dominant data-center software ecosystem. However, unlike Nvidia or Qualcomm, which integrate their AI technology into their own proprietary chips, Quadric remains an IP licensor. This model aims to avoid locking customers into a specific vendor’s silicon roadmap. Comparison of AI Semiconductor Approaches: Company Business Model Key Differentiator Target Market Quadric Licenses programmable AI processor IP Software-updatable, avoids vendor lock-in Embedded devices, laptops, automotive Nvidia Sells complete GPU chips and systems Dominant CUDA software ecosystem for data centers Cloud data centers, high-performance computing Qualcomm Sells complete SoCs with integrated AI Strong presence in mobile and connected devices Smartphones, laptops, XR headsets Synopsys/Cadence Sells fixed-function NPU IP blocks Integrated into broader chip design toolflows Broad semiconductor industry The Distributed AI Infrastructure Imperative The economic rationale for distributed, on-device inference is becoming increasingly compelling. The rising cost of operating massive, centralized AI cloud infrastructure is a burden for many enterprises. Additionally, numerous countries lack the resources or geographic suitability to build hyperscale data centers. This reality prompts greater interest in setups where AI inference runs locally—on laptops, smartphones, or small on-premise servers within office buildings. The World Economic Forum recently highlighted this architectural shift. It noted the movement of AI inference closer to end-users and away from purely centralized models. This trend reduces latency, enhances data privacy, and can lower operational expenses. For a startup like Quadric, this macro shift represents a vast and growing total addressable market. The company now employs nearly 70 people worldwide, with teams in San Francisco and Pune, India, to service this global opportunity. Conclusion: A Promising Trajectory with Execution Ahead Quadric’s rising revenue and valuation clearly demonstrate that the market for on-device AI inference is not just theoretical—it is generating real economic value today. The company has successfully positioned itself at the intersection of several powerful trends: the need for cost-effective AI, the demand for technological sovereignty, and the requirement for hardware that can adapt to rapidly evolving software models. Its programmable, licensable IP model offers a distinct alternative to both merchant chip vendors and traditional IP block suppliers. Nevertheless, the company acknowledges it is still in the early phases of its buildout. While it has secured several key design wins and signed customers, its long-term success hinges on converting these licensing agreements into high-volume product shipments and the recurring royalty streams they generate. The strategic pivot from cloud to on-device AI inference is undeniably underway. For Quadric, riding this wave has already begun to pay off spectacularly, setting the stage for the next chapter in the distributed intelligence era. FAQs Q1: What is on-device AI inference, and why is it important? On-device AI inference refers to running trained artificial intelligence models directly on a local device—like a laptop, smartphone, or car computer—instead of sending data to a remote cloud server for processing. This approach is crucial for reducing latency, lowering cloud costs, enhancing data privacy, and enabling functionality in areas with poor connectivity. Q2: How does Quadric’s business model differ from companies like Nvidia or Qualcomm? Quadric does not manufacture or sell physical chips. Instead, it licenses the intellectual property (IP) design for a programmable AI processor. Customers integrate this “blueprint” into their own custom silicon designs. This contrasts with Nvidia (sells complete GPU hardware) and Qualcomm (sells complete system-on-chip packages), offering clients more flexibility and avoiding vendor lock-in. Q3: What is “sovereign AI,” and how does it relate to Quadric’s strategy? Sovereign AI is a national or organizational strategy to develop and control domestic AI capabilities—including compute infrastructure, data, and models—to reduce dependence on foreign technology providers. Quadric is exploring this market by offering its IP to companies and governments in regions like India and Malaysia, helping them build local AI hardware expertise. Q4: What are the main challenges of designing hardware for AI? The primary challenge is the rapid evolution of AI model architectures (e.g., from CNNs to Transformers), which can happen in months, while hardware design and manufacturing cycles typically span years. Quadric addresses this by offering programmable IP that can be updated via software to support new models without a full chip redesign. Q5: What markets is Quadric targeting beyond automotive? While Quadric started in automotive for applications like driver assistance, it has significantly expanded. Its technology now targets AI-powered laptops, industrial IoT devices, printers, and other edge computing applications where local, efficient AI processing provides a competitive advantage. This post On-Device AI Surge: Quadric’s Strategic Pivot from Cloud to Edge Inference Pays Off Spectacularly first appeared on BitcoinWorld .
22 Jan 2026, 12:04
Vitalik Buterin Proposes Built-In DVT to Simplify Ethereum Staking
Ethereum ETH co‑founder Vitalik Buterin has introduced the idea of embedding distributed validator technology (DVT) right into the Ethereum protocol to simplify staking processes.
22 Jan 2026, 11:00
Danes develop apps to boycott American products over Greenland tension
Mobile apps allowing users to avoid American products have been enjoying growing popularity in Denmark amid cross-Atlantic tensions over the future of Greenland. While it’s yet to be seen if the software will significantly affect consumption of the already rare “Made in USA” goods, it’s certainly giving Danes a chance to vent out a little over President Trump’s appetite toward the Danish territory. ‘WithoutUSA’ app overtakes ChatGPT by downloads in Denmark Applications that help identify American-made items in the supermarket are becoming a hit in Denmark, its national radio broadcaster revealed. Two locally developed apps, “Made O’Meter” and “UdenUSA,” are seeing the most downloads, according to a report by Danmarks Radio (DR) on Wednesday. UdenUSA, or “WithoutUSA” was created by 21-year-old Jonas Pipper and his 22-year-old friend Malthe Hensberg, both from the island of Mors in western North Jutland. It all started last spring when they discovered a Facebook group called “Boykot USA,” which had nearly 100,000 users at the time, Pipper told the radio’s online edition, adding: “Then we thought – that’s funny, there’s no tool to scan a product and find out where it comes from.” Their UdenUSA app is now used for precisely that purpose – allowing Danes to identify the origin of goods, before they put them in the shopping cart, and find alternatives from countries other than the U.S., if they so wish. The application is now trending and has become the fourth most downloaded on Apple’s App Store in Denmark, overtaking OpenAI’s ChatGPT , which is currently fifth, DR Nyheder noted in the post. Its developers claim their software is merely a consumer tool and their intention is not to tell compatriots whether they should actually boycott certain goods. “We’re just providing the opportunity to have a little more clarity, and then it’s up to the consumers what they want to do,” explained Jonas Pipper. Will the boycott actually work beyond venting anger? Gauging the impact of apps of this kind is a difficult task, as these days, it’s not that easy to find truly American-made products on supermarket shelves in Denmark anyway, comment the authors of the report. “When we look at imports, very little comes directly from the U.S.,” remarked Louise Aggerstrøm Hansen, private economist at Danske Bank. While there are examples of popular items, including some wines and almonds, directly imported American foods account for less than 1.2% of the Danish diet. Besides, many of the products offered by American brands are not produced in the United States and may even be manufactured in Denmark itself. However, even if it doesn’t bring down big U.S. corporations, participation in the boycott movement would make Danes feel they are reacting somehow to the current conflict, according to Pelle Guldborg Hansen from the Roskilde University. “A lot of people watch the news and see something they don’t like and get angry about. In this case, it’s about ourselves and Greenland, and then you just want to do something with your anger, no matter how small it is,” the behavioral researcher explained, adding: “More people see changing their consumption patterns as a move they can make. It may not seem like much, but it’s still something. And it’s a way of expressing their anger.” Choices made at the store can redirect consumption, and even if Coca-Cola doesn’t notice it’s selling less in Denmark, a Danish company like the Harboe brewery may feel it, Hansen elaborated. The Trump administration’s renewed push to, one way or another, acquire Greenland for the United States, citing national security reasons, caused heightened tensions between Europe and America in the past weeks. Earlier in January, the U.S. President warned he’s going to impose trade penalties on countries opposing the acquisition and then even threatened NATO member states that don’t agree with his plan with tariffs that may eventually reach 25%. The European Union responded by halting the parliamentary approval of a transatlantic trade agreement with Washington reached last summer. During his participation in the global economic forum in Davos this week, Donald Trump backtracked on his intention to slap tariffs on European nations and ruled out using military force to take over Denmark’s island, an option he had previously left open. Join a premium crypto trading community free for 30 days - normally $100/mo.
22 Jan 2026, 10:32
Vitalik Buterin Proposes Fix to Ethereum Staking — No More Single-Node Risk
Vitalik Buterin, the co-founder of Ethereum, has suggested the fundamental alteration to the staking system in the network to eliminate the dependency on one validator node. In a detailed post published Wednesday on the Ethereum Research forum, Buterin introduced the idea of “native distributed validator technology,” or native DVT. Source: ethresear.ch The idea would allow stakers to split validator responsibilities across multiple nodes directly at the protocol level rather than relying on complex external setups. Ethereum’s Staking Boom Brings New Security Questions The proposal comes as Ethereum staking reaches record scale with more than 36 million ETH now staked across nearly one million validators, with the total value of staked assets exceeding $118 billion. Source: ValidatorQueue . While this growth has reinforced Ethereum’s security, it has also amplified long-standing concerns around centralization, operational risk, and the technical barriers faced by solo stakers. For much of Ethereum’s proof-of-stake history , running a validator meant placing 32 ETH behind a single machine and a single private key. Any failure, from a power outage to a software bug or security breach, could result in inactivity penalties or slashing. These risks pushed many users toward large staking providers and liquid staking platforms, concentrating control of consensus among a relatively small group of operators and cloud providers. Buterin’s proposal directly targets that single-node risk, as under the proposed native DVT, a validator with a larger balance would be allowed to register multiple keys, up to a maximum of 16, and define a threshold for signing duties. Validator actions, such as block proposals or attestations, would only be considered valid if a minimum number of those keys signed off together. As long as more than two-thirds of the nodes behave honestly, the validator would continue operating normally without penalties. Buterin’s Native DVT Idea Targets Easier, Safer ETH Staking Unlike existing DVT solutions such as Obol or ssv.network, which rely on external tooling, networking layers, and the linear properties of BLS signatures, Buterin’s design would be embedded directly into Ethereum’s consensus rules. He argued this would dramatically simplify staking operations, reduce setup complexity, and remove dependencies that may not be compatible with future cryptographic upgrades . @VitalikButerin unveils "The Splurge," a bold plan to prepare Ethereum for a quantum future! #Ethereum #QuantumComputing https://t.co/vvRijeahpS — Cryptonews.com (@cryptonews) October 29, 2024 From a user perspective, Buterin described the experience as running multiple standard validator nodes with minimal configuration changes. Most of the added complexity would be limited to block production, where one node would act as a temporary leader and others would co-sign its output. The proposal is explicitly aimed at medium- to large-sized ETH holders , including institutions and individual “whales,” who currently face a choice between running fragile single-node setups or outsourcing control to staking providers. By making multi-node staking simpler, Buterin said native DVT could increase client diversity, improve measurable decentralization metrics, and encourage more self-custodial staking. Ethereum Developers Debate Practical Challenges of the DVT model The discussion quickly drew technical feedback from the community. Ethereum developer Alonmuroch raised questions around coordination during block production, the possibility of multiple proposers racing to collect signatures, and the need for protocol-level key rotation to handle compromised keys without forcing validators to exit and re-stake. Buterin largely agreed, noting that instant key changes should be feasible and that reducing operational headaches is central to the proposal’s motivation. The proposal also fits into a broader shift in Buterin’s recent public messaging. Earlier this month, he declared 2026 the year Ethereum would reclaim lost ground on self-sovereignty and trustlessness, calling for fewer compromises in favor of convenience. Days later, he warned that Ethereum risks becoming an “unwieldy mess” if developers continue layering complexity onto the protocol without deliberate simplification. The post Vitalik Buterin Proposes Fix to Ethereum Staking — No More Single-Node Risk appeared first on Cryptonews .
22 Jan 2026, 10:15
OpenAI in talks with Middle Eastern sovereign funds on $50B round
OpenAI is working to raise fresh capital from investment funds controlled by Middle Eastern governments, according to sources who spoke with CNBC this Wednesday. The company hopes to bring in roughly $50 billion through this financing effort, though the final amount may shift since formal agreements haven’t been completed yet. A close source shared these details on the conditio n th eir name not be used because the information remains private. Altman travels to UAE as funding round takes shape Sam Altman, who leads OpenAI as its chief executive, traveled to the United Arab Emirates to take part in the investment conversations, the source confirmed. The company expects to wrap up this funding round during the first three months of the year. OpenAI set off the current wave of interest in artificial intelligence when it released ChatGPT, its conversational AI tool, back in 2022. Since that launch, the company has grown into one of the world’s most rapidly expanding commercial operations. It has pulled in many billions of dollars from backers while working to build larger systems, create improved technology, and add new capabilities. The company completed a $40 billion investment round last year with SoftBank taking the lead role. That deal set a record as the biggest private technology funding ever documented. Microsoft, which has been a central investor for years, joined that round along with Coatue, Altimeter and Thrive. OpenAI also finished selling $6.6 billion worth of shares this past October. That transaction pushed the company’s total value to $500 billion. NVIDIA partnership brings major infrastructure investment The firm recently made another major announcement involving NVIDIA. The two companies said they plan to work together in what they’re calling a landmark arrangement. Under this deal, NVIDIA will provide at least 10 gigawatts of its computing systems for OpenAI’s upcoming AI infrastructure. OpenAI will use these systems to train and operate its next wave of models as it works toward what it calls superintelligence. To make this happen, including building data centers and securing power capacity, NVIDIA plans to put up to $100 billion into OpenAI as the new systems get installed. The first portion of this setup should start running in the second half of 2026 using NVIDIA’s Vera Rubin platform. “NVIDIA and OpenAI have pushed each other for a decade, from the first DGX supercomputer to the breakthrough of ChatGPT,” said Jensen Huang, founder and CEO of NVIDIA. “This investment and infrastructure partnership mark the next leap forward — deploying 10 gigawatts to power the next era of intelligence.” “Everything starts with compute,” said Sam Altman. “Compute infrastructure will be the basis for the economy of the future, and we will utilize what we’re building with NVIDIA to both create new AI breakthroughs and empower people and businesses with them at scale.” OpenAI will treat NVIDIA as its main partner for computing and networking as it grows what it calls its AI factory. The two companies will coordinate their plans so OpenAI’s model and infrastructure software work well with NVIDIA’s hardware and software. OpenAI now counts more than 700 million people using its services each week. The company has also seen strong uptake from large corporations, smaller companies and people who build software. This new partnership with NVIDIA should help OpenAI move forward with its stated goal of building artificial general intelligence that helps everyone. NVIDIA and OpenAI said they expect to nail down the remaining details of this new phase of their partnership within the next few weeks. div]:bg-bg-000/50 [&_pre>div]:border-0.5 [&_pre>div]:border-border-400 [&_.ignore-pre-bg>div]:bg-transparent [&_.standard-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.standard-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8 [&_.progressive-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.progressive-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8"> _*]:min-w-0 gap-3 standard-markdown"> While OpenAI conducts these major negotiations, other American AI companies are putting down roots in the Middle East right now. Verkada, which makes AI-powered security technology for physical spaces, said it’s expanding into the region by opening an office in Dubai and hiring Fred Crehan to run Middle East operations. If you're reading this, you’re already ahead. Stay there with our newsletter .
