Polymarket And Kalshi Rivalry Forging New Paths In Prediction Markets

by THEFUTURE.TEAM

March 24, 2026

High-Stakes Competition In A Booming Market

The prediction market sector is seeing growing competition between Polymarket and Kalshi, two startups that are expanding their positions while also converging around a shared investment initiative. Both companies are linked to 5(c) Capital, a new fund focused on opportunities within the prediction market space. Despite their rivalry, the involvement of both sides in the same fund highlights a broader alignment around the sector’s long-term potential.

Innovative Funding Initiative

5(c) Capital, named after the regulatory clause governing prediction markets, is raising $35 million for its first fund. The initiative is backed by key figures in the sector, including Kalshi CEO Tarek Mansour and Polymarket CEO Shayne Coplan, alongside established investors.

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The fund plans to invest in around 20 companies, with a focus on infrastructure such as market makers and index development. These areas are seen as critical for supporting the growth and functionality of prediction markets.

A Strategic Investment By Industry Leaders

Kalshi has confirmed that its CEO is backing the fund, signalling confidence in the sector’s development. While Polymarket has not publicly detailed its position, its leadership’s involvement points to a similar outlook. The fund is led by Adhi Rajaprabhakaran, a former Kalshi trader, and Noah Zingler-Sternig, previously head of operations at Kalshi, bringing sector-specific experience into the investment strategy.

Expanding Market Valuations

At the same time, valuations across the sector are increasing. Kalshi is in the process of raising $1 billion at a valuation of $22 billion, roughly double its level from four months earlier. Polymarket is also in discussions for a new funding round, with a reported valuation target of around $20 billion. These figures reflect growing investor interest in prediction markets and their potential role within financial technology.

Looking Ahead

The combination of rising valuations, new capital and increased competition suggests continued expansion in the sector. The launch of 5(c) Capital adds further support to infrastructure development, which could play a key role in shaping how prediction markets evolve. At the same time, the involvement of competing players in shared initiatives highlights how the market is still forming, with collaboration and competition developing in parallel.

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Meta Unveils Muse Wonder Models In A Bid For Frontier AI Leadership

by THEFUTURE.TEAM

October 13, 2026

Meta has introduced two new AI models, Muse Wonder and Muse Wonder Full, signalling a more ambitious move into frontier AI. The releases build on Muse Spark but target more demanding tasks, including coding, while placing greater emphasis on long-term memory and personalised assistance.

Larger Models Target More Demanding Tasks

Unlike Muse Spark, which was designed for low latency and lightweight use, Muse Wonder and Wonder Full are significantly larger and, according to Meta, more capable. The company reports stronger benchmark performance and improvements on demanding workloads, including coding.

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According to Meta’s model card, both models achieved benchmark results comparable to Fable 5.1 and GPT-6 Astra in the company’s internal testing. Meta described the release as “the next step on our scaling ladder and a major leap toward personal superintelligence” in its announcement.

Pricing Reflects Meta’s Frontier Ambitions

The models’ pricing places them in the premium AI segment. Through the Meta Model API, Muse Wonder will cost $4 per million input tokens and $20 per million output tokens, putting it in a similar pricing tier to GPT-6 Sol and Opus 5.5.

Muse Wonder Full, by contrast, will not be offered through the API. Meta says it will be exclusive to Muse Code subscribers, tying access to its most advanced model to a premium product. Both models will also power the Muse agent.

Long-Term Memory Takes Centre Stage

Meta is increasingly positioning its AI strategy around assistants that can support users over time rather than respond only to individual prompts. A central part of that approach is what the company calls “active memory”: the ability to retain, organise and synthesise information provided by users across extended periods.

Meta points to the MemoryBench benchmark, which evaluates systems designed for continual learning and memory construction. The company says Muse Wonder now outperforms Fable, Opus and Astra on this measure.

“We put a tremendous amount of effort into making sure your model can remember what’s important to you over days, weeks, months, and beyond,” research scientist Kavya Kopparapu said in a launch video.

New Models Follow Meta’s AI Reorganisation

The launch is also significant within Meta’s broader AI strategy. It is the company’s first frontier-model release since Scale AI founder Alexandr Wang reorganised its AI operations in August 2025. Meta has since introduced Muse Spark and the Muse agent, while making fewer high-profile model announcements than competitors such as OpenAI and Anthropic.

The new models were trained at Meta’s Prometheus data centre in central Ohio, which came online earlier in 2026, according to the company. The facility highlights the growing importance of infrastructure in the race to develop advanced AI systems, where performance depends not only on algorithms and data but also on computing capacity, data-centre investment and access to capital.

As competition intensifies, Muse Wonder and Wonder Full represent a broader bet on larger models, persistent memory and premium AI products. Their longer-term significance will depend on how their reported capabilities translate into real-world performance and whether users find enough value to pay for access.

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