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Últimas Noticias de IA
How a former DeepMind researcher raised at a $300M pre-seed valuation before launching a product
Andrew Dai left Google DeepMind knowing visual AI was the frontier he wanted to stake his claim in. He pulled off a whirlwind fundraise that resulted in a more aggressive valuation-to-capital ratio thanThinking Machines, which raised one of the largest rounds in U.S. history. In this episode ofBuild Mode,host and Startup Battlefield lead Isabelle Johannessen sits down with Andrew Dai, founder and CEO ofElorianand former Google DeepMind researcher, to discuss how his company raised a $55 million seed round at a $300 million valuation just months after leaving Google. Drawing on more than a decade spent helping build some of the world’s most influential AI systems, including research that later informed the development of ChatGPT, Andrew explains why he believes visual AI is one of the next major frontiers in artificial intelligence. “You have models that are doing really great at math, really great at new physics ideas, and of course coding is very popular now … But one area where progress has been extremely uneven is visual understanding and visual reasoning,” said Dai. “At Elorian, we want to build models that will advance us toward visual AGI.” Andrew walks through the fundraising process from the founder’s perspective, including how he refined a highly technical vision into a compelling story investors could understand. He explains why he prioritized strategic partners like Nvidia and Menlo Ventures over even higher valuation offers, and how choosing investors who understood the realities of building frontier AI proved more valuable than simply maximizing his company’s price tag. The conversation also offers practical lessons for founders navigating today’s rapidly evolving AI landscape. Andrew shares how startups can communicate complex technical ideas without relying on jargon, why speed has become one of the biggest competitive advantages in AI, and what it takes to recruit world-class researchers away from Big Tech. Loading the player… This season on Build Mode, we’re diving into all aspects of fundraising with experts who have firsthand experience raising massive pre-seed rounds, writing the big checks, bootstrapping, going public, and navigating the unexpected market circumstances that can change everything. Subscribe to Build Mode onApple Podcasts,Spotify, orwherever you like to listen. And watch the full videos onYouTube. New episodes of Build Modedrop every Thursday.
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UP's Data Centre Policy Wins Industry Backing, Faces Execution Test
Uttar Pradesh has won industry support for its AI-ready vision, but executives say reliable renewable power and execution will determine its long-term success.
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Bengaluru-Based Mandrake Bio Raises ₹16 Crore to Build AI-Designed Gene Editors
The funding will help the startup scale its AI protein design platform and validate gene editors for agricultural and medical applications.
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AI-Driven Distribution Is Changing How Fintechs Reach India's Underserved
WeRize replaces branch networks with AI-managed freelance agents, using more than 20 billion proprietary data points.
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Wipro Posts Muted June Quarter; AI-Led Transformation Deals Lift Large Bookings
Wipro reported muted June-quarter earnings, with constant currency revenue rising less than 1% and margins contracting.
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Tech Mahindra’s AI Bets Help Lift Margins as Q1 Profit Rises 28%
Tech Mahindra posts double-digit revenue and profit growth as AI engineering, sovereign AI investments and large transformation deals support margin expansion.
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Codex Micro Launched as a Dedicated Controller for OpenAI Codex Power Users: Price, Features
OpenAI has launched the Codex Micro in global markets. The new keyboard, developed in association with keyboard maker Work Louder, is designed to work with the company's AI coding assistant Codex. It can be used to switch between agents and start new chats instantly. The Codex Micro includes a joystick for navigation and a rotary dial for adjusting the agent's reasoning level. It offers Codex integration and lets users remap commands, adjust layouts, and more, without requiring additional software downloads. The latest hardware device by OpenAI is designed for developers working with agentic workflows.
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Google’s AI Product Sprawl Is Confusing Developers
And how Google is working hard to fix it.
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Synchrony Opens its Largest Global Experience Center in Hyderabad
The new facility highlights India’s growing role in technology, AI and enterprise capabilities across Synchrony’s global operations.
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Madhya Pradesh Courts Semiconductor, AI and Data Centre Firms with Investment Proposals Worth Over ₹58,000 Crore
The largest proposals came from Submer India Private Limited, which expressed interest in investing ₹19,000 crore to develop data centre infrastructure
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Google Upgrades Gmail Help Me Write With Custom AI Email Edits
Google has introduced a new update for Gmail's Gemini-powered Help Me Write feature that gives users greater control over AI-generated email drafts. The latest addition allows people to refine existing drafts using their own text instructions instead of relying only on preset editing options. The update also adds undo and redo controls for AI edits, making it easier to revise messages before sending them. Google says the feature is rolling out now and is expected to reach eligible users by July 20.
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Applied Computing wants to give oil and gas operators an AI model for the entire plant
Applied Computing, a London-based startup that’s building a foundation AI model for the oil, gas, and petrochemical industry, has raised a $20 million Series A led by engineering giant KBR, with Databricks Ventures participating. Founded in 2023, the startup targets oil, gas, refining, and petrochemical systems, where a single facility can have thousands of sensors measuring everything from temperature and pressure to velocity and viscosity. While there’s ahuge marketfor helping energy companies solve the data-tracking problem, the fragmentation presents a significant hurdle.Facilities consequently make operating decisions using less than 8% of the data available to them, says Applied Computing’s co-founder and CEO Callum Adamson (pictured above, right). Operators already collect much of this information, he said, but they struggle to combine the sensor readings, engineering documentation, and physics and chemistry quickly enough to analyze and make predictions.“It’s getting those three data sources to talk to each other in real time. That’s the real key,” he told TechCrunch.Unlike large language models, which predict the next word, Applied Computing says its foundation model, Orbital, combines a time series model, a physics-based model, and a language model to predict the state of a facility. It does this by analyzing sensor readings, keeping physics and chemistry in mind, and recognizing a facility’s equipment constraints and operator activity. It also allows technicians to run simulations of how a change in one part of a facility could affect the rest of its operations. Essentially, Applied Computing is pitching speed: It claims Orbital can flag anomalies, investigate what caused them, and model whether a proposed fix could create problems elsewhere in the facility, all within minutes. Adamson claims the product can compress investigations that previously took days or weeks into seconds, helping operators reduce energy use and maintain output. That promise of speed seems to have found believers. The startup says it has gone from stealth to double-digit millions in annual recurring revenue in under 18 months. Adamson said Orbital is in use at some “large, publicly listed” upstream oil and gas, downstream refining and petrochemicals companies, although he declined to mention how many customers it has. Its partners include Indian energy company Wipro, and KBR, which has integrated Orbital into its INSITE 3.0 digital platform for energy projects, and is using the product for ammonia production. Adamson said the startup is also working with a “major U.S. upstream operator” and plans to announce a partnership with a European oil major in the coming weeks. Still, Applied Computing is entering a market that has entrenched industrial software suppliers, as well as more focused AI startups.AspenTechsells simulation and AI-powered modeling software for upstream, refining, and chemical operations, whileAVEVAoffers physics-based process simulation, optimization, and “what-if” modeling for industrial plants.CogniteandSeeqtarget the data layer, helping facilities analyze industrial data, and apply AI to design workflows. Adamson argues that the company’s moat is not access to industrial data or process knowledge, but rather assembling AI researchers to build a model that can compete with Orbital.“It’s an AI problem. It’s not a data problem, and it’s not an energy problem,” he said. “If you’re a tier-one AI researcher, where are you going to work? … I don’t think Shell’s on that list.” Adamson also pointed to the data Orbital receives through its deployments. Operational data from refineries and other energy facilities is generally not available publicly, he said, while simulated data cannot fully reproduce what happens inside a working plant. The KBR partnership may help the company, too. Adamson said the partnership gives Applied Computing access to operational data and industry expertise, as well as introductions to more potential customers. Applied Computing plans to use the $20 million to expand internationally, hire for research and engineering roles, and explore deployments with energy clients. The company on Thursday said it’s also opened an office in Houston, adding to its headquarters in London and operational hub in Bengaluru. Adamson said the U.S. base puts the startup closer to two existing customers in North America, and an expansion into the Middle East is also in the works.
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