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Today’s exploration:

• 💰 Contextual AI raise $20M

• 🕵️‍♂️ 3 Job opportunities at Contextual

• 🤑 $71m in other funding announcements

Read time: 4 minutes

🔥 Contextual AI

💻 What’s Their Product/Service?

Contextual AI is a new enterprise-focused AI startup founded by AI veterans from Facebook AI Research (FAIR) and Hugging Face. Their unique focus is developing ASI—artificial specialised intelligence. The startup's mission is to solve enterprise problems by using AI that is custom-built for their needs, rather than a one-size-fits-all solution.

They are questioning the need for AI to be a jack-of-all-trades, suggesting that having a model that knows Shakespeare and quantum physics might be unnecessary if all it should really do is solve your company’s problem. This innovative approach positions Contextual AI as a pioneering force in the world of enterprise AI solutions.

📖 Their Story So Far:

Contextual AI was founded by Douwe Kiela and Amanpreet Singh, both of whom have impressive experience in the realm of AI and large language models (LLMs). They previously worked at Meta Platforms’ FAIR, developing systems for detecting hate speech in memes and the sale of illicit goods on Facebook. At Hugging Face, they further honed their skills working on LLMs.

The launch of Contextual AI signals their desire to apply their skills to address six key problems they've identified for enterprises wanting to use LLMs: data privacy, customisability, hallucinations, compliance, staleness, and latency and cost. They're particularly critical of the staleness of current AI models, with a pointed reference to the fact that OpenAI's ChatGPT doesn't know anything that happened after September 2021, and BERT still thinks Obama is president.

Their commitment to the open source AI community is also noteworthy. They believe in the importance of diversifying control over such a disruptive technology, and plan to both leverage and contribute to open source software.

🔮 Future Plans

With a team size of 12 so far, Contextual AI aims to grow its workforce to close to 20 people by the end of 2023.

They plan to spend the majority of their seed funding on product development. A significant portion of the investment will be channeled towards building a compute cluster to train LLMs. They are determined to drive the development of enterprise-grade AI, and their backers have expressed confidence in their potential to make AI more secure, integrated, and most importantly, contextual to employee workflows.