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The TAO Subnet Team Praised by Jensen Huang Has Parted Ways with the Founder Amidst a Fallout

Nvidia CEO Jensen Huang recently praised the decentralized AI project Bittensor (TAO) during a podcast, specifically highlighting a 72-billion-parameter Llama model trained collaboratively by a subnet team called Covenant AI. This endorsement initially boosted TAO's price, but the situation deteriorated rapidly when Covenant AI's founder, Sam Dare, publicly announced the team's departure from the Bittensor network. Covenant AI accused Bittensor and its key figure, Jacob Steeves (known as Const), of centralization and abuse of power, contradicting Bittensor’s decentralized ethos. The team claimed that Const exercised unilateral control by halting subnet emissions, removing administrative rights, discarding infrastructure, and using token sales to pressure the team. They argued that Bittensor’s governance is effectively centralized under Const, despite claims of distributed control. As a result, Covenant AI decided to leave, intending to continue its work on decentralized AI training elsewhere. The exit has sparked significant concern within the Bittensor community, raising doubts about the network’s decentralization narrative, technical future, and token value. TAO’s price fell sharply following the news. Const responded vaguely on social media, suggesting the event would push Bittensor toward more decentralized, “headless” subnets, but has not addressed the specific allegations in detail. The incident has damaged Bittensor’s reputation while raising Covenant AI’s profile.

Odaily星球日报04/10 03:08

The TAO Subnet Team Praised by Jensen Huang Has Parted Ways with the Founder Amidst a Fallout

Odaily星球日报04/10 03:08

5.4 Billion Burned, Sora Dies: Anonymous Chinese Model Kicks Open the Next Door in 38 Seconds

In March-April 2026, two major events reshaped the AI video generation landscape. OpenAI shut down its flagship model Sora, citing unsustainable daily costs of $15 million and low user retention, effectively exiting the consumer video market. Shortly after, an anonymous Chinese model dubbed "HappyHorse-1.0" topped the blind-test leaderboard on Artificial Analysis with a score of 1357 in text-to-video (without audio), outperforming rivals like ByteDance’s Seedance 2.0. HappyHorse-1.4 seconds to generate 1080p video with audio on a single H100 GPU. Its unified Transformer architecture and distilled diffusion techniques significantly improved efficiency compared to Sora’s costly diffusion-based approach. The model is speculated to be developed by Alibaba or based on Sand.ai’s technology, though its anonymous release suggests strategic data collection and legal risk avoidance regarding copyright and deepfake regulations. Meanwhile, commercial leaders like ByteDance impose high barriers—including million-dollar API contracts and strict compliance checks—to mitigate legal risks, focusing on B2B applications rather than consumer use. Key emerging opportunities include automated e-commerce promo videos, AI-assisted short drama production, and localized ad creation for global markets, all driven by plunging generation costs and faster turnaround times. The competition has shifted from pure model performance to cost efficiency, workflow integration, and regulatory compliance.

marsbit04/10 00:19

5.4 Billion Burned, Sora Dies: Anonymous Chinese Model Kicks Open the Next Door in 38 Seconds

marsbit04/10 00:19

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