Serena Williams: “I Would Have Been Banned For 20 Years” If I Failed Drug Tests Like Sinner

by News Editor

April 17, 2025

Serena Williams, one of tennis’s most iconic figures, has claimed she would have been handed a 20-year ban and stripped of her Grand Slam titles had she failed drug tests like Jannik Sinner did last year. Serena Williams, who retired in 2022 with 23 Grand Slam singles titles to her name, has long been one of tennis’s most dominant players.

Sinner, the world number one in men’s tennis, accepted a three-month ban earlier this year after the World Anti-Doping Agency (WADA) challenged an independent tribunal’s ruling clearing him of wrongdoing despite testing positive for clostebol, an anabolic steroid. The Italian player maintains his innocence, but the case sparked questions about possible preferential treatment from the authorities. His suspension will be lifted on May 4, 2025.

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In the interview, Williams expressed admiration for Sinner, describing him as a talented player who is “great for the sport.” However, she also highlighted the double standards that seem to exist in tennis, pointing out that had she been in Sinner’s position, the consequences would have been far more severe.

“I love the guy, love this game. He’s great for the sport. I’ve been put down so much, I don’t want to bring anyone down. Men’s tennis needs him,” Williams stated. “But, if I did that, I would have gotten 20 years. Let’s be honest. I would have gotten Grand Slams taken away from me.”

Her comments bring attention to the perceived inconsistencies in the way drug testing and bans are applied in tennis. While Sinner’s suspension remains relatively short, high-profile cases such as Iga Świątek’s one-month ban in November for testing positive for trimetazidine and Simona Halep’s controversial four-year ban for roxadustat use (which was reduced to nine months following an appeal) have ignited further debate.

Williams also shared that she always took extra precautions to ensure she didn’t unknowingly ingest anything that could potentially cause trouble, reflecting the heightened vigilance required by athletes to avoid the risk of unintentional doping violations.

As the sport continues to confront doping issues, questions around consistency and fairness in the application of sanctions remain key talking points.

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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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