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$AI Especially at the intersection of Crypto and AI, a brand new narrative—AI Layer 1 (abbreviated as AI L1)—is quietly emerging. Here, "Layer 1" does not refer to public chains, but rather to the foundational layer of AI technology, encompassing the basic tech stack and frameworks of AI agents, and even including AI agent token launch platforms similar to pump.fun, from which enormous value can be captured for their tokens.$AI $AIXBT

The world of artificial intelligence$AI has experienced its fair share of ups and downs. From the hype of the 1980s to the decline of the 1990s and early 2000s, AI has been on a rollercoaster ride. However, with the current AI spring in full bloom, it's essential to look back at the decline of previous AI projects and identify which ones are worth watching .The Decline of AI Projects The decline of AI projects can be attributed to several factors, including.Overhyped Expectations The AI community's tendency to overpromise and underdeliver led to disappointment and reduced funding.Lack of Practical Applications Many AI projects focused on theoretical research rather than practical applications, making it difficult to secure funding.Competition from Other Technologies The rise of other technologies, such as expert systems and machine learning, drew attention and funding away from AI.Notable AI Projects That Declined Some notable AI projects that declined include.The Fifth Generation Project A $850 million project launched by the Japanese government in 1981 to develop AI systems that could converse, translate languages, and reason like humans. The project failed to meet its objectives and ended in 1992.The Strategic Computing Initiative A DARPA-funded project launched in 1983 to develop AI systems for military applications. The project was cut back due to lack of progress and funding.The LISP Machine Market A market that emerged in the 1980s for specialized computers that could run LISP, a programming language used in AI research. The market collapsed in 1987 due to the rise of alternative technologies. AI Projects to Watch Despite the decline of previous AI projects, there are several new and exciting projects worth watching:Chain AI Projects Projects that focus on developing AI systems that can learn and reason like humans, such as Google's DeepMind and Microsoft's Cognitive Toolkit. Natural Language Processing (NLP) Projects Projects that focus on developing AI systems that can understand and generate human language, such as IBM's Watson and Stanford's Natural Language Processing Group.Computer Vision Projects Projects that focus on developing AI systems that can interpret and understand visual data, such as Google's Computer Vision API and Facebook's FAIR.In conclusion, while the decline of previous AI projects is a cautionary tale, it's essential to recognize the potential of new and emerging AI projects. By learning from the past and focusing on practical applications, we can ensure that AI continues to advance and improve our lives.

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AI agents are far more than simple chatbots. Especially at the intersection of Crypto and AI, a brand new narrative—AI Layer 1 (abbreviated as AI L1)—is quietly emerging. Here, "Layer 1" does not refer to public chains, but rather to the foundational layer of AI technology, encompassing the basic tech stack and frameworks of AI agents, and even including AI agent token launch platforms similar to pump.fun, from which enormous value can be captured for their tokens.$AI $AIXBT

DeepSeek R1 stand out is its efficiency—it matches or surpasses the performance of leading models like those from OpenAI, but it was built on a modest $6 million budget and uses significantly fewer GPUs. While this breakthrough is a huge leap for AI, it has rattled the market for AI-related crypto assets as investors reassess the value of tokens tied to GPU-intensive operations. Render (RNDR), Near Protocol (NEAR), The Graph (GRT), and Artificial Superintelligence Alliance (FET) are among the hardest hit, with losses ranging from 7% to 9%. Node.AI (GPU), which is heavily reliant on GPU-based operations, has seen a staggering 20% drop. Altogether, the total market cap of AI-focused cryptocurrencies has shrunk by 8%, now sitting at $38 billion. This sell-off created a ripple effect, spilling over into the broader crypto market and pulling down even mainstream assets like Bitcoin and Ethereum. The cascading losses can be partly explained by liquidations, a phenomenon that often amplifies price movements. Over the past 24 hours, nearly $942 million in futures positions have been liquidated, with an overwhelming $830 million of these being long positions. This stark imbalance between long and short liquidations clearly shows how unprepared traders were for the rapid sell-off triggered by the fallout from DeepSeek’s release. Liquidations of this scale often create a vicious cycle — falling prices force more liquidations, which in turn accelerates the downward spiral. As a result, the market goes into a freefall. At the same time, the macroeconomic environment is adding more pressure. $AI $EARNM