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Project Overview
Parallel is a science fiction trading card game (TCG) that uses non-fungible tokens (NFTs) to give players ownership of their cards and other game assets. The cards can be used to construct a deck and play in an online client or mobile game, which is currently in development.
Former Twitter CEO Launches AI Startup Parallel Web Systems, Raises $100M in Series B Funding with $2B Valuation
According to The Wall Street Journal, Parallel Web Systems—an AI startup founded by former Twitter CEO Parag Agrawal—has raised $100 million in its Series B funding round, led by Sequoia Capital, with participation from Kleiner Perkins, Index Ventures, and Khosla Ventures. The company’s valuation has risen to $2 billion, bringing its total funding to $230 million. Parallel focuses on building web search infrastructure for AI agents, supporting in-depth research use cases such as investment research, insurance claims processing, and government contract analysis. Over 100,000 developers are already using its platform, with customers including legal AI company Harvey. Proceeds from this round will be used to expand the sales team and strengthen R&D efforts.
Tempo Launches Privacy Solution Zones, Supporting Permissioned Parallel Blockchains
According to The Block, Layer 1 blockchain Tempo has launched a privacy solution called Zones, designed for institutional use cases such as payroll distribution, treasury management, and payment settlement. Zones provide a confidential execution environment in the form of parallel blockchains connected to the Tempo mainnet; transactions within a Zone are confidential by default, yet assets remain interoperable with the Tempo mainnet, other Zones, fiat on/off-ramps, and liquidity pools. Tempo states that each Zone will be managed by a trusted entity, whose operators can view activities within the Zone and enforce access controls—but do not control the underlying assets. Users retain full control and may withdraw funds locked in smart contracts on the mainnet at any time.
Related news
xAI Case Reveals Challenges of Large-Scale GPU Parallel Utilization: "Buying" AI Computing Power ≠ "Using It Well"
the latest practices from xAI show that even after successfully acquiring a large number of Nvidia server-grade GPUs, how to utilize them efficiently remains one of the core bottlenecks in AI training.As AI developers continue to compete for Nvidia computing resources, the tight supply of GPUs has been widely recognized. However, the new challenge for the industry lies in "utilization efficiency" itself. AI model training typically exhibits a distinctly "bursty" nature: GPUs operate intensively for short periods, then enter idle phases for result analysis and strategy adjustments.This uneven pattern of computing power usage makes it difficult for large-scale GPU clusters to maintain consistently high utilization rates, resulting in significant waste of computing power even when hardware is abundant.Industry insiders point out that this issue is forcing AI companies to redesign training architectures and scheduling systems to improve the overall utilization efficiency of GPU clusters, rather than simply expanding the scale of computing power. (The Information)
Former Twitter CEO Launches AI Startup Parallel Web Systems, Raises $100M in Series B Funding with $2B Valuation
According to The Wall Street Journal, Parallel Web Systems—an AI startup founded by former Twitter CEO Parag Agrawal—has raised $100 million in its Series B funding round, led by Sequoia Capital, with participation from Kleiner Perkins, Index Ventures, and Khosla Ventures. The company’s valuation has risen to $2 billion, bringing its total funding to $230 million. Parallel focuses on building web search infrastructure for AI agents, supporting in-depth research use cases such as investment research, insurance claims processing, and government contract analysis. Over 100,000 developers are already using its platform, with customers including legal AI company Harvey. Proceeds from this round will be used to expand the sales team and strengthen R&D efforts.
Tempo Launches Privacy Solution Zones, Supporting Permissioned Parallel Blockchains
According to The Block, Layer 1 blockchain Tempo has launched a privacy solution called Zones, designed for institutional use cases such as payroll distribution, treasury management, and payment settlement. Zones provide a confidential execution environment in the form of parallel blockchains connected to the Tempo mainnet; transactions within a Zone are confidential by default, yet assets remain interoperable with the Tempo mainnet, other Zones, fiat on/off-ramps, and liquidity pools. Tempo states that each Zone will be managed by a trusted entity, whose operators can view activities within the Zone and enforce access controls—but do not control the underlying assets. Users retain full control and may withdraw funds locked in smart contracts on the mainnet at any time.