A new path to artificial general intelligence (AGI) is being charted by Logical Intelligence, a San Francisco-based startup founded by Eve Bodnia. The company's focus is on developing an energy-based reasoning model (EBM), which absorbs parameters and completes tasks within those confines, eliminating mistakes and requiring less compute.
The EBM approach differs from large language models (LLMs), which rely on prediction algorithms to guess the next word in a sequence. In contrast, EBMs are able to self-correct and reason independently, using data that is sparse rather than exhaustive. This method is expected to be more efficient and accurate, particularly in tasks that require complex problem-solving.
Logical Intelligence's debut model, Kona 1.0, has already demonstrated its capabilities by solving sudoku puzzles significantly faster than leading LLMs. The company expects to apply this technology to various industries, including the energy sector and pharmacology, where data processing is critical.
The startup's decision not to open-source its EBM technology yet reflects a commitment to ensuring its stability and effectiveness before sharing it with the public. Bodnia views her role as a responsible creator, aiming to ensure that her work contributes positively to society.
While Logical Intelligence's path diverges from the conventional approach of developing LLMs, it shares a common goal: to create AI systems that can assist humans in various domains. The startup's focus on EBM is part of an ecosystem of compatible AI models that will enable AGI when fully developed.
The EBM approach differs from large language models (LLMs), which rely on prediction algorithms to guess the next word in a sequence. In contrast, EBMs are able to self-correct and reason independently, using data that is sparse rather than exhaustive. This method is expected to be more efficient and accurate, particularly in tasks that require complex problem-solving.
Logical Intelligence's debut model, Kona 1.0, has already demonstrated its capabilities by solving sudoku puzzles significantly faster than leading LLMs. The company expects to apply this technology to various industries, including the energy sector and pharmacology, where data processing is critical.
The startup's decision not to open-source its EBM technology yet reflects a commitment to ensuring its stability and effectiveness before sharing it with the public. Bodnia views her role as a responsible creator, aiming to ensure that her work contributes positively to society.
While Logical Intelligence's path diverges from the conventional approach of developing LLMs, it shares a common goal: to create AI systems that can assist humans in various domains. The startup's focus on EBM is part of an ecosystem of compatible AI models that will enable AGI when fully developed.