Kalshi Targets $40 Billion Valuation as Prediction Markets Industry Splits in Two
Prediction markets platform Kalshi is reportedly seeking a valuation of around $40 billion in its latest fundraising efforts, nearly triple the $15 billion valuation target being pursued by rival Polymarket. The development highlights a growing divide within the rapidly expanding prediction markets industry, where companies are taking sharply different approaches to growth and regulation.
Kalshi has emerged as one of the most prominent players in the sector by operating within a regulated framework in the United States. The company allows users to trade contracts based on the outcomes of real-world events, including elections, economic data releases, weather events and sporting outcomes. Its emphasis on regulatory compliance has helped attract significant investor interest and positioned it as a leading name in financial technology.
The company’s ambitious valuation target reflects the increasing popularity of prediction markets, which have gained attention as alternative platforms for information gathering and speculative trading. Investors appear to be betting that these markets could eventually become mainstream tools for forecasting future events and measuring public sentiment.
Meanwhile, Polymarket has built its business around a crypto-native model that uses blockchain technology and digital assets. The platform has attracted a large international user base and gained prominence during major global events. However, its decentralized approach has also exposed it to regulatory scrutiny in several markets.
The contrasting valuation targets underscore a broader split taking shape in the industry. On one side are regulated platforms like Kalshi that are seeking deeper integration with traditional finance and institutional investors. On the other are crypto-focused platforms like Polymarket that prioritize decentralization, global participation and blockchain-based infrastructure.
As investor enthusiasm for prediction markets continues to grow, competition between the two models is intensifying. The outcome of this rivalry could shape the future of online forecasting and determine whether regulated exchanges or decentralized platforms become the dominant force in one of the financial technology sector’s fastest-growing segments.
After Taking Nvidia’s Money, Odyssey Raises $310 Million and Bets on Amazon and AMD Instead
Artificial intelligence infrastructure startup Odyssey has raised $310 million in fresh funding, even as it shifts its computing strategy away from a heavy reliance on Nvidia and expands partnerships with rivals Amazon and AMD.
The latest funding round marks another major vote of confidence in companies building the backbone of the AI economy. Odyssey plans to use the new capital to expand its computing infrastructure and accelerate the development of AI services aimed at enterprise customers.
The company had previously received investment from Nvidia, whose graphics processing units have become the gold standard for training and deploying advanced artificial intelligence models. However, rising demand for AI chips, limited supply and increasing costs have prompted many technology companies to seek alternatives to Nvidia’s ecosystem.
Odyssey’s decision to deepen its relationships with Amazon and AMD reflects a broader trend unfolding across the AI industry. Businesses are increasingly looking to diversify their sources of computing power rather than relying on a single supplier. By tapping Amazon’s cloud infrastructure and AMD’s growing portfolio of AI accelerators, Odyssey hopes to build a more flexible and cost-efficient platform.
The move also highlights intensifying competition in the AI infrastructure market. While Nvidia continues to dominate the sector, competitors are rapidly investing in technologies designed to challenge its leadership. Cloud providers and chipmakers alike are racing to capture a larger share of the booming demand for AI computing resources.
For Odyssey, the strategy represents both a business opportunity and a risk-management decision. Depending heavily on one chip supplier can expose companies to supply constraints and pricing pressures, especially as AI adoption accelerates across industries.
The fresh funding provides Odyssey with significant resources to pursue its expansion plans at a time when investors remain eager to back companies positioned to benefit from the artificial intelligence boom. As demand for AI infrastructure continues to surge, the company’s willingness to diversify beyond Nvidia’s ecosystem could offer it greater resilience and a competitive edge in an increasingly crowded market.
Enterprise AI Adoption Hits Record Highs, but ROI Remains Unproven. Can ‘Tokenmaxxing’ Close the Gap?
Enterprise adoption of artificial intelligence has surged to record levels as companies race to incorporate generative AI into their operations. From automating customer support and generating marketing content to assisting software development and data analysis, businesses are increasingly embracing AI as a strategic priority.
Yet, despite widespread implementation and significant spending, proving the financial return on these investments remains a major challenge.
Many organisations have moved quickly from experimentation to deployment, integrating AI tools across departments in hopes of improving productivity and gaining a competitive advantage. However, executives are increasingly asking difficult questions about whether these initiatives are delivering measurable outcomes. While AI systems may boost efficiency in certain tasks, translating those gains into clear revenue growth, cost savings or improved profitability has proven far more complicated.
The disconnect between rising adoption and uncertain returns has led to growing interest in a concept known as “tokenmaxxing.” The term refers to maximising the value derived from every token processed by AI models. Rather than focusing solely on increasing AI usage, the approach encourages companies to optimise how they use AI so that each interaction generates meaningful business results.
Advocates of tokenmaxxing argue that enterprises should prioritise high-impact applications, carefully select AI models for specific tasks and refine prompts and workflows to improve outcomes while reducing computing costs. The goal is to ensure that AI deployments are not only technologically impressive but also economically efficient.
The concept reflects a broader shift in the corporate AI landscape. The first phase of generative AI adoption was characterised by rapid experimentation and fear of falling behind competitors. The next phase is likely to be defined by accountability, efficiency and measurable value creation.
As businesses continue to expand their AI investments, the debate is increasingly moving beyond how quickly AI can be adopted and toward how effectively it can deliver tangible returns. In that environment, tokenmaxxing is emerging as a potential framework for bridging the gap between AI enthusiasm and proven business value.
Why Meta Wants CRED: The $4 Billion Fintech Deal That Could Reshape India’s Payments Industry
Meta is reportedly considering a deal involving Indian fintech startup CRED at a valuation of around $4 billion, a move that could significantly alter the competitive landscape of India’s digital payments sector.
India has become one of the world’s most attractive markets for digital financial services. The country processes billions of digital transactions every month and has witnessed rapid growth in mobile payments, online commerce and financial technology adoption. For global technology companies, India represents both a massive user base and a crucial opportunity to expand beyond social media and advertising.
Despite the popularity of WhatsApp, Facebook and Instagram in India, Meta has struggled to establish a meaningful presence in the country’s payments ecosystem. While WhatsApp Pay has gained traction, it continues to face intense competition from established players that dominate digital transactions and consumer payments.
CRED could offer Meta an attractive route into the market. Since its launch, the Bengaluru-based company has developed a strong brand among financially active and creditworthy consumers. What began as a platform for credit card bill payments has evolved into a broader fintech ecosystem that includes lending, shopping, rewards and financial services.
For Meta, acquiring or partnering with CRED would provide access to a highly engaged user base and an established financial infrastructure. Such a deal could allow the company to integrate payments and financial products more deeply into its platforms, creating a seamless experience that combines communication, commerce and transactions.
The potential transaction also reflects a broader trend among technology companies seeking to build digital ecosystems where users can interact, shop and manage finances without leaving a single platform. India’s rapidly expanding digital economy makes it an ideal testing ground for these ambitions.
If the deal materialises, it could accelerate innovation in India’s fintech industry and intensify competition among digital payment providers. More importantly, it could mark a significant step in Meta’s efforts to transform from a social media company into a broader digital services and financial technology platform.
