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OpenAI’s Revenue Hits $4.3bn in First Half of 2025, But Cash Burn Remains Heavy

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OpenAI generated about $4.3 billion in revenue in the first half of 2025, according to financial disclosures to shareholders reviewed by The Information. The figure represents a 16% jump over its total revenue for all of 2024, underscoring the scale of demand for artificial intelligence tools like ChatGPT.

At the same time, the disclosures show the AI company is still spending aggressively to secure its lead. OpenAI reported a cash burn of $2.5 billion in the first six months of the year, largely driven by the immense cost of running and developing large-scale AI models.

Heavy R&D Spending

The report highlights that OpenAI poured $6.7 billion into research and development during the period, a level of spending unmatched in the sector. Even after such outlays, the company closed the half-year with $17.5 billion in cash and securities, giving it substantial firepower to pursue expansion despite mounting costs.

OpenAI told investors it expects to meet its full-year revenue goal of $13 billion while keeping cash burn within its $8.5 billion target.

Valuation and Liquidity Moves

The financial disclosures land as OpenAI continues to explore ways to broaden its capital base. In August, Reuters reported the company was in early discussions about a stock sale allowing employees to cash out, a move that could value the firm at roughly $500 billion. Such secondary sales are increasingly common among late-stage private companies as they balance high valuations with the need to retain talent.

Investor appetite remains strong for Nvidia, which has benefited enormously from the AI boom. The company announced last week that it will invest up to $100 billion in OpenAI and supply data-center chips critical to scaling the company’s operations. The partnership links OpenAI more closely to the dominant supplier of AI infrastructure, ensuring a steady pipeline of computing power even as rivals like Anthropic, Google DeepMind, and xAI expand their own model development.

How OpenAI Stacks Up

While OpenAI’s revenue trajectory is the steepest in the industry, its burn-to-revenue ratio is far higher than its peers. By comparison, Google DeepMind — folded into Google’s broader AI division — is estimated to spend several billion annually, but Alphabet’s vast advertising revenues cross-subsidize those costs, shielding investors from the kind of direct burn rate OpenAI is shouldering.

Anthropic, backed by Amazon and Google, has pursued a more measured growth strategy. Its last reported figures suggested annualized revenue in the low billions, but with lower infrastructure costs as it leaned heavily on its cloud backers for credits and partnerships. xAI, Elon Musk’s entrant, has raised billions but is still at an earlier stage of monetization, focusing on consumer subscriptions and integrations with Tesla and X.

In this context, OpenAI’s $6.7 billion R&D spend in just six months signals both its scale and its structural disadvantage: unlike DeepMind, it lacks a parent company with diversified revenue streams, and unlike Anthropic, it must sustain massive compute costs more directly on its balance sheet.

The Assumptions

For financial markets, OpenAI’s numbers highlight the paradox of generative AI: surging top-line growth paired with eye-watering costs. Investors are expected to interpret the $4.3 billion revenue haul as validation of enterprise adoption and ChatGPT’s stickiness, but the $6.7 billion R&D spend underlines how capital-intensive the race for model dominance has become.

Behaviorally, the disclosures may harden a view among investors that only a handful of players — those with access to vast computing resources and strategic partners like Nvidia — can realistically compete at scale. At the same time, the looming $500 billion valuation could spark debate in financial circles about whether OpenAI is entering “mega-cap tech” territory in private markets, or whether its cash burn points to a model that will remain structurally expensive for years.

With OpenAI signaling confidence in its full-year revenue and cash-burn targets, markets may treat its disclosures as evidence that the AI wave remains in full force — but also as a reminder that profitability, not just scale, is the long-term hurdle.

Tekedia Capital Joins Paul Graham, Others To Seed Nozomio with $6.2m

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Tekedia Capital joins Paul Graham (a founder of YCombinator), executives in OpenAI, and other global investors to seed Nozomio, with $6.2 million, under the solo and singular one-person coding prodigy Arlan Rakhmetzhanov.

Arlan’s story is a magical one: from Kazakhstan to Silicon Valley for an advanced context augmentation system for AI agents . We wish this secondary school dropout the best of luck as he takes Nozomio to the next level.

I started Nozomio in high school six months ago as an AI agent for codebases that could cross-reference multiple repos, answer questions, and help developers onboard themselves. I failed.

But I knew there was something in the agent space that every developer wants: the right context.

Right before my Y Combinator batch, I was struggling to give coding agents the right context. They missed versions, filled up the context window, and used incorrect frameworks. That is when I built the first iteration of Nia, which is now an augmentation layer for AI agents.

Context is the most important problem in the agent space. It prevents AI systems from achieving superhuman code intelligence, and I want to solve it.

The current state of Nia might change a thousand times, but the problem will stay the same. Even as an MCP, which is very novel and underdeveloped, Nia has already improved every coding agent by at least 30%. I am on the mission to 100x it.

Periodic Labs Emerges from Stealth With $300m Funding, Aiming to Build AI Scientists for Materials Discovery

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Periodic Labs, a startup founded by some of the most influential minds in artificial intelligence, launched out of stealth on Tuesday with a massive $300 million seed round.

The funding, unusually large for a company at this stage, reflects the ambition of its mission: to automate scientific discovery through AI-driven laboratories.

The round was backed by an elite roster of investors from both the tech and scientific worlds, including Andreessen Horowitz, DST, Nvidia, Accel, Elad Gil, Jeff Dean, Eric Schmidt, and Amazon founder Jeff Bezos.

From AI Breakthroughs to Scientific Frontiers

Periodic Labs was founded by Ekin Dogus Cubuk and Liam Fedus. Cubuk previously led the materials and chemistry team at Google Brain and DeepMind, where he helped develop GNoME, an AI tool that discovered more than 2 million new crystals in 2023—materials researchers say could one day power entirely new generations of technology.

Fedus, meanwhile, is a former VP of Research at OpenAI and one of the creators of ChatGPT. He also led the team behind the first trillion-parameter neural network. The company’s small team is composed of scientists and engineers who have worked on major AI and materials science initiatives, including OpenAI’s agent Operator and Microsoft’s MatterGen, a large language model for materials discovery.

Automating Discovery

Periodic Labs describes its mission as building “AI scientists.” In practice, this means creating labs where robots conduct experiments, collect data, and learn from each cycle, iterating in ways that mimic and potentially accelerate the scientific method.

The startup’s first focus is superconductors—materials capable of conducting electricity with little to no resistance. Today’s superconductors are expensive, difficult to produce, and require extreme conditions like supercooling. If Periodic Labs can invent new materials that perform better under easier conditions, it could reshape industries from power transmission to computing.

Another priority is building a vast database of physical-world data generated by its AI scientists. “Until now, scientific AI advances have come from models trained on the internet,” the company said in a blog post. But with the internet as a data source now “exhausted,” Periodic Labs argues that the next breakthroughs will depend on fresh, real-world experimental data.

A Field Heating Up

While Periodic Labs is one of the most heavily funded entrants in this space, it is not alone. Automating chemistry and materials discovery with AI has been a growing focus of academic research since at least 2023. Startups such as Tetsuwan Scientific, nonprofits like Future House, and institutions like the University of Toronto’s Acceleration Consortium are also exploring how machine learning can accelerate breakthroughs in materials science.

But Periodic’s $300 million seed round sets it apart. It represents one of the largest initial financings for a science-focused AI company and suggests that Silicon Valley’s top investors believe the combination of AI and lab automation could lead to transformative discoveries.

Beyond AI Chatbots

The launch highlights a broader shift in the AI sector. For years, breakthroughs like ChatGPT and generative image models have defined public understanding of AI. But with models trained largely on the internet reaching diminishing returns, investors are now backing ventures that can create their own experimental data.

Companies like Periodic Labs hope to do for physical science what ChatGPT did for language: compress decades of trial-and-error into accelerated cycles of learning. Compared with efforts in pharmaceuticals, where AI is already being used to predict drug candidates, materials discovery has lagged. Periodic’s deep pockets and star-studded founding team suggest that may soon change.

The opportunity is believed to be about scale: creating not just one AI scientist, but many, each running thousands of experiments to invent materials that today exist only in theory.

BlockDAG’s F1® Power Move vs Algorand’s Growth & VeChain’s Roadmap: Which Is the Top Crypto Coin for 2025?

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BlockDAG’s bold sponsorship of the BWT Alpine Formula 1® Team has placed it firmly in the spotlight, adding global visibility to an already growing ecosystem. At the same time, Algorand has reported a 66% increase in transactions and nearly 69% surge in whale holdings, signaling rising institutional interest. VeChain, while quieter in market movement, continues to refine its utility roadmap with staking upgrades, interoperability tools, and enterprise adoption.

But among these three, BlockDAG (BDAG) is the only protocol combining real-world marketing firepower with verified infrastructure rollout.

With nearly $415 million raised in its presale, more than 26.5 billion BDAG coins sold, and a current ROI of 2900% since Batch 1, BlockDAG is not just a promotional story, it’s a functioning ecosystem priced at $0.0015, despite Batch 30 pricing at $0.03. For investors looking for the top crypto coins 2025, this is a rare blend of technical substance and branding reach.

BlockDAG: From Presale to Pit Lane

BlockDAG has made its mark by turning a crypto presale into a multimedia campaign. The partnership with the BWT Alpine Formula 1® Team puts the BDAG brand on one of the most competitive racing platforms on Earth. Race car branding, digital experiences, fan zones, and activation events at high-visibility races like the Singapore Grand Prix and Token2049 create a feedback loop of trust, reach, and community participation.

But this is more than just branding. BlockDAG’s core infrastructure is rolling out in real time. Its Awakening Testnet is now live, and features miner syncing, explorer tools, DAG + PoW consensus, and account abstraction, all of which solidify its long-term value proposition. The presale itself speaks volumes: nearly $415 million raised, a locked price of $0.0015, despite Batch 30 pricing at $0.03, and an ROI of 2900% since Batch 1.

With over 26.5 billion coins sold and 20,000+ physical miners shipped, BlockDAG is delivering tech and traction. While other Layer?1s struggle to distinguish themselves in a saturated market, BlockDAG is driving both adoption and awareness by meeting users on-chain and offline. These moves place it at the front of the line when discussing the best crypto to buy now.

Algorand: Metrics with Momentum

Algorand has always emphasized technical rigor, and its latest numbers indicate renewed attention. According to on-chain data from September 21, 2025, transaction volume surged 66% week-over-week. Even more significantly, whale holdings increased by approximately 68.77%, suggesting that large investors are regaining confidence.

However, despite the surge in network activity, ALGO’s price remains stuck between $0.16 and $0.25, with a critical Fibonacci resistance at $0.25 blocking any immediate breakout. For Algorand to transition from accumulation to price discovery, it will need to break above this threshold with strong volume.

That said, the protocol’s core architecture based on fast, low-cost, and secure smart contract execution remains intact. It continues to be a go-to platform for developers looking for scalability without sacrificing decentralization. Still, it lacks the real-world partnerships or mass-market branding needed to drive retail excitement.

VeChain: Silent Utility, Steady Foundations

VeChain offers a different kind of crypto story. It trades quietly at around $0.025, showing minimal volatility but maintaining strong utility fundamentals. While its price action is subdued, VeChain has consistently built partnerships in supply chain management, real-world asset tokenization, and enterprise integration.

The recently announced “Renaissance” roadmap upgrades VeChain’s protocol governance, staking models, and interoperability frameworks. These changes are geared toward making VeChain a more robust platform for enterprise use cases, especially in logistics, food safety, carbon tracking, and luxury goods authentication.

Still, the lack of retail-facing marketing and slow-moving token price can dampen speculative interest. Unlike BlockDAG, which is attracting attention through visual dominance and product rollouts, VeChain’s growth is institutional and methodical. It’s unlikely to generate overnight returns, but its utility-driven foundation may reward long-term holders.

Final Thought

In the race toward 2025, BlockDAG, Algorand, and VeChain each bring strengths, but BlockDAG leads in execution and visibility. Algorand’s network growth is meaningful, and VeChain continues to deliver enterprise-grade infrastructure. Yet only BlockDAG combines crypto presale momentum, real-world sponsorship, and live technical rollouts.

With nearly $415 million raised, 26.5 billion coins sold, a 2900% ROI from Batch 1, and a presale still offering $0.0015 pricing, BlockDAG offers unmatched upside. Its sponsorship with the BWT Alpine Formula 1® Team is more than marketing; it’s validation. For those seeking the top crypto coins 2025, BlockDAG’s trajectory looks the most complete and compelling.

Presale: https://purchase.blockdag.network

Website: https://blockdag.network

Telegram: https://t.me/blockDAGnetworkOfficial

Discord: https://discord.gg/Q7BxghMVyu

Predictive Oncology Launches a $344.4M Digital Asset Treasury

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Aethir, the leading provider of decentralized AI compute, announced that Predictive Oncology, a leader in AI-driven drug discovery, will amass a $344,4 million strategic compute reserve purpose built to acquire and stake ATH, the network token of Aethir.

The initiative, spearheaded by DNA Fund, a leading crypto and Web3 investment and advisory firm, and banked by BTIG is structured as a public-market vehicle and marks the first time a Nasdaq-listed company will hold and actively manage tokens of a decentralized physical infrastructure network.

The GPU shortage has emerged as one of the most significant barriers to scientific progress, constraining everything from pharmaceutical research to climate modeling.

In oncology, training AI models to analyze massive genomic and patient datasets requires sustained access to high-performance compute, yet costs on centralized cloud providers remain prohibitively high and availability limited.

Our partnership with Aethir represents a seminal event for Predictive Oncology and we believe it creates an outstanding opportunity for the Company and our shareholders to solidify and expand our core business while embarking upon an incremental growth opportunity through our digital asset treasury strategy, commented Raymond Vennare, Chief Executive Officer and Chairman of the Board of Predictive Oncology.

DNA Holdings Venture, Inc will serve as the Company’s strategic advisor and consultant for the digital asset treasury. DNA Fund is one of the original venture capital firms in the Web3 space, led by early crypto pioneers.

The ATH Treasury directly links institutional capital with Aethir’s global GPU infrastructure, providing investors exposure to one of the fastest-growing decentralized physical infrastructure networks (DePIN).

“This is a watershed moment for the global compute problem,” said Daniel Wang, Co-founder and CEO of Aethir. “This ATH Treasury functions as a strategic compute reserve that not only validates the demand for more GPU infrastructure at the institutional level, it also provides a compliant and transparent structure for public-market investors to participate in the explosive AI compute cycle through Aethir.”

Aethir’s decentralized marketplace sources, verifies, and orchestrates enterprise-grade GPU supply, offering cost savings to centralized providers. With more than $150 million in verifiable on-chain ARR, Aethir is among the most commercially scaled projects in the DePIN category, serving enterprise clients across AI, gaming, and high-performance computing.

To date, Aethir has already delivered 1.16 billion compute hours, and over 340 million in Q3 alone, up 17.5% quarter-over-quarter. This total output is equivalent to training a model with over 7 trillion parameters in 30 days. This scale translates into real-world impact: faster AI innovation, democratized access to enterprise-grade GPUs, and 40–80% savings versus hyperscalers.

By accumulating and staking ATH, Predictive Oncology will strengthen the security and decentralization of the Aethir network while enabling institutional investors to participate in its growth without direct token custody.

Through Aethir’s unique network mechanisms, ATH can also be converted into physical GPUs, providing a direct pathway from token exposure to productive compute capacity.

About Aethir

Aethir is a decentralized cloud computing infrastructure platform delivering enterprise-grade GPU access for artificial intelligence, machine learning, and cloud gaming applications. Operating one of the largest decentralized Physical Infrastructure Networks (DePIN), Aethir connects GPU suppliers with enterprises through a global footprint of 430,000+ GPUs across 200+ deployment sites in 90+ countries.

With $150M+ in annual recurring revenue and backing from leading investors including Framework Ventures, Hashkey, Animoca Brands, and more, Aethir provides scalable, utility-driven infrastructure that lowers costs and expands access to compute worldwide.

About Predictive Oncology 

Predictive Oncology is on the cutting edge of the rapidly growing use of artificial intelligence and machine learning to expedite early drug discovery and enable drug development for the benefit of cancer patients worldwide.

The company’s scientifically validated AI platform, PEDAL, is able to predict with 92% accuracy if a tumor sample will respond to a certain drug compound, allowing for a more informed selection of drug/tumor type combinations for subsequent in-vitro testing.

Together with the company’s vast biobank of more than 150,000 assay-capable heterogenous human tumor samples, Predictive Oncology offers its academic and industry partners one of the industry’s broadest AI-based drug discovery solutions, further complimented by its wholly owned CLIA laboratory facility.