Venture Bytes #103: AI Start-ups Bringing Efficiency in EV Battery Mineral Exploration
AI Start-ups Bringing Efficiency in EV Battery Mineral Exploration
As the EV adoption accelerates, the demand for critical battery minerals such as lithium, nickel, and cobalt is soaring. EVs could constitute 56% of US passenger vehicle sales by 2030, per estimates from energy organization RMI. This growth brings to the fore a critical challenge: meeting the escalating demand for key battery minerals.
The demand for these minerals is growing at an unprecedented rate. For instance, to meet the 2030 EV demand, lithium production must quadruple from 490,000 tons in 2021 to 2 million tons, per EY.
Without additional mining development, the lithium market could face a deficit of 700,000 tons by 2030. The copper market, similarly, is projected to experience a deficit of nearly 4.7 million tons by 2030. Data from RMI and Kobold Metals also suggests a shortfall between the expected demand and the available supply of key battery materials. KoBold Metals estimates that the industry needs to discover more than
$12 trillion worth of new critical mineral deposits to stop catastrophic climate change.
These figures underscore a looming supply crisis, exacerbated by inept current mineral exploration methods. Today’s mineral exploration predominantly relies on manual techniques, resulting in a process that is not only time-consuming and less efficient but also leads to discoveries that are often unexpected and unpredictable. Out of 1,070 mineral sites discovered between 2008 and 2018, only 19 turned out to be Tier 1 (or World Class), per data from MinEx Consulting. The research further suggests that the mineral exploration sector has seen a shift from generating net value to diminishing it. Despite an expenditure of $198 billion on exploration, the sector only produced $109 billion in value, reflecting an efficiency ratio of 0.55, indicating that for every dollar spent, the sector is now generating less than half the value it once did.
In this challenging scenario, AI-driven startups like KoBold Metals and Earth AI are stepping up as pivotal players. These startups leverage AI, ML, and advanced data analytics to offer greater precision, efficiency, and a higher success rate in locating viable mineral deposits. California-based KoBold Metals, which raised a
$200 million Series C round in June 2023, is building a full-stack digital prospecting engine for battery mineral exploration. Backed by Andreessen Horowitz, Bill Gates’ Breakthrough Energy Ventures, Bond Capital, BHP Ventures, and Sam Altman’s Apollo Projects, the company has collaborated with various mining companies including BHP and Rio Tinto, the two largest mining companies in the world by market cap.
Also based in California, Earth AI is a vertically integrated mineral exploration technology company operating in unexplored greenfield terrains. The company, which helps mining explorers increase their chances of mineral discovery and lower operational risks and costs, recently announced the first discovery of a greenfield molybdenum deposit using artificial intelligence in Australia.
Additionally, policy initiatives from the federal government have significantly propelled the shift toward the advancement of battery production. The Infrastructure Investment and Jobs Act alongside the Inflation Reduction Act have set up close to $30 billion in subsidies and tax credits for the EV supply chain based on Congressional Budget Office figures.
The energy transition is set to drive significant financial commitments, with the mining and metals industry facing the prospect of a $1.7 trillion outlay in the next decade and a half to ensure adequate availability of critical metals like copper, cobalt, and nickel (EY). Closing the gap in copper supply demands a substantial $100 billion, and the expansion of lithium production capacity is estimated to need a $21 billion infusion by 2025. Amidst growing enthusiasm for establishing a self-reliant lithium-battery production line in the US, startups are emerging as potential key players, poised to supply innovative software solutions that enhance cost efficiency and operational effectiveness for mining firms.**
User Retention Key to Generative AI Success
The moat of generative AI platforms is tied to the quality of the databases on which they are trained. However, with several generative AI models getting trained on similar databases, this moat will be unsustainable in the long run. The enduring moat for generative AI startups will stem from user retention as the robustness of LLMs lies in continuous learning through user interactions and feedback. Currently, most generative AI startups are battling to capture a high DAU/MAU (daily active user/monthly active user) percentage. For reference, consumer applications such as WhatsApp, Instagram, and YouTube, among others have a median DAU/MAU of 51%, significantly higher than the 14% for generative AI apps, per Sequoia.
In this race for high customer retention, Character.ai and Runway hold pole positions, boasting leading DAU/MAU readings of 41% and 27%, respectively. These two startups have demonstrated that success extends beyond possessing powerful models, providing a personalized, efficient user experience that fosters loyalty. The formidable combination of an elevated user experience, distinctive features, and robust customization options presents a formidable barrier to swift replication by competitors. Prioritizing user engagement and cultivating a loyal customer base positions such startups strategically for long-term value accumulation and sustainability.
Character.ai, a California-based generative AI platform, is leveraging generative AI for entertainment services. The platform allows users to engage with AI chatbots emulating celebrities and pop culture icons, thus showcasing considerable viral potential. In March 2023, the startup secured $190 million series A funding at a $1 billion valuation, affirming investor confidence. With a user base exceeding 20 million globally, and a predominant 60% falling within the 18 to 24 age brackets, Character.ai demonstrates significant popularity and precise targeting. Projected to attain a
$16.7 million annual revenue in 2024, per Demand Sage, the startup is primed for financial growth. Capitalizing on its users’ average two-hour engagement, the startup holds the potential to generate significant revenue from advertisements. Boasting over 5 million app downloads worldwide and 16 million user-created chatbots on the platform, Character.ai emerges as a potential disruptor, poised to revolutionize dialogue creation in the entertainment industry. Character.ai’s iOS and Android apps have garnered 4.2 million monthly active users in the US, closing in on 6 million monthly active users on ChatGPT’s mobile apps, per Similarweb.
Runway is valued at $1.5 billion and has raised a total of $236.5 million to date. Founded in 2018, Runway stands as a prominent generative AI platform specializing in video creation and editing, featuring an expansive arsenal of over 30 AI tools. Positioned as a comprehensive solution for multimedia content creators, Runway has garnered substantial financial support from tech titans like Google and NVIDIA, reinforcing its industry credibility. The recent funding round, resulting in a remarkable 200% increase in valuation, serves as a testament to investor confidence in the company’s potential. The platform’s clientele, including notable names like CBS, the Yankees, and Nickelodeon, further bolsters its credibility in the market. Runway’s ability to significantly reduce editing time, exemplified by transforming The Late Show’s
workflow from hours to minutes, demonstrates the technological prowess of the platform. Various creatives attest that one hour in Runway is equivalent to hours of editing in Adobe Premiere Pro, a leading video editing software. In addition to time savings, Runway strategically appeals to both customers and investors through cost optimization. The platform offers a range of subscription options, including a free tier for videos up to 60 seconds, a standard account at $12 per month, an advanced Pro account at $28 per month, and a flagship unlimited account at $76 per month. This competitive pricing model contrasts sharply with traditional VFX costs, where projects like a 30-second promotional video typically incur expenses ranging from $1,500 to $2,500, as reported by
What’s a Rich Text element?
The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
Static and dynamic content editing
A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!
How to customize formatting for each rich text
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.