State of AI Report 2020
State of AI Report

              

              
                The State of AI Report analyses the most interesting developments in AI. We aim to trigger an informed conversation about the state of AI and its implication for the future. The Report is produced by AI investor Nathan Benaich and Air Street Capital.
              

              

              
              Download 2024 Report

              
              
                
              
              

              
              
                
              
              

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              📧 Air Street PressNow in its seventh year, the State of AI Report 2024 is reviewed by leading AI practioners in industry and research. It considers the following key dimensions, including a new Safety section:
                  Research: Technology breakthroughs and their capabilities. 
                  Industry: Areas of commercial application for AI and its business impact. 
                  Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI. 
                  Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us. 
                  Predictions: What we believe will happen and a performance review to keep us honest. 
              


              Key takeways from the 2024 Report include::
                Frontier lab performance begins to converge and proprietary models lose their edge, as the gap between GPT-4 and the rest closes. OpenAI o1 put the lab back at the top of the charts - but for how long?
                Planning and reasoning take priority in LLM research, as companies explore combining LLMs with reinforcement learning, evolutionary algorithms, and self-improvement to unlock future agentic applications.
                Foundation models demonstrate their ability to break out of language, supporting multimodal research across mathematics, biology, genomics, the physical sciences, and neuroscience.
                US sanctions have limited effects on Chinese labs’ ability to produce capable models, as a combination of stockpiles, approved hardware, smuggling, and cloud access allow them to build highly performant (V)LLMs. Meanwhile, China’s efforts to build a domestic semiconductor industry remain scrambled.
                The enterprise value of AI companies has hit $9T, as public companies experience a bull market for AI exposure. Investment in private AI companies also increased, but by an order of magnitude less, despite GenAI megarounds in the US.
                A handful of AI companies begin to generate serious revenue,  including foundation model builders and start-ups working on video and audio generation. However, as models get cheaper as part of the corporate land-grab, questions around long-term sustainability go unanswered.
                The pseudo-acquisition emerges as an off-ramp for AI companies, as some companies struggle to find a viable business model as staying at the frontier proves costly.
                The existential risk discourse has cooled off, especially following the abortive coup at OpenAI. However, researchers have continued to deepen our knowledge of potential model vulnerabilities and misuse, proposing potential fixes and safeguards.
                
              

              

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