Thinking Machines debuts Inkling 2 Small amid reported $5B fundraising push

Thinking Machines Labs Inc. released Inkling 2 Small, a large language model that automates artificial intelligence training tasks, late Thursday. Around the same time, Business Insider reported that Thinking Machines is raising a $5 billion funding round led by Accel. The model release and the reported raise position the company at the intersection of AI training tooling and large-scale investor interest.

Thinking Machines debuts Inkling 2 Small amid reported $5B fundraising push SiliconANGLE https://siliconangle.com Thinking Machines Labs Inc. has released a new large language model https://www.machinebrief.com/glossary/large-language-model that can automate artificial intelligence https://www.machinebrief.com/glossary/artificial-intelligence training https://www.machinebrief.com/glossary/training tasks. The algorithm, Inkling 2 Small, made its debut late Thursday. Around the same time, Business Insider reported that Thinking Machine is in the process of raising a $5 billion funding round led by Accel. The company, which … The post Thinking Machines debuts Inkling 2 Small amid reported $5B fundraising push https://siliconangle.com/2026/11/06/thinking-machines-debuts-inkling-2-small-amid-reported-5b-fundraising-push/ appeared first on SiliconANGLE https://siliconangle.com . Get AI news in your inbox Daily digest of what matters in AI. Key Terms Explained Artificial Intelligence https://www.machinebrief.com/glossary/artificial-intelligence The science of creating machines that can perform tasks requiring human-like intelligence — reasoning, learning, perception, language understanding, and decision-making. Language Model https://www.machinebrief.com/glossary/language-model An AI model that understands and generates human language. Large Language Model https://www.machinebrief.com/glossary/large-language-model An AI model with billions of parameters trained on massive text datasets. Training https://www.machinebrief.com/glossary/training The process of teaching an AI model by exposing it to data and adjusting its parameters to minimize errors.