Stay Ahead In AI

Enterprises increasingly rely on large language models (LLMs) to deliver advanced services, but struggle to handle the computational costs of running models. A new framework, chain-of-experts (CoE), aims to make LLMs more resource-efficient while increasing their accuracy on reasoning tasks. 

As more U.S. companies incorporate generative AI tools into the workplace, job posts related to the technology are increasing, including a new type of job title: generative AI management consultant, according to a Feb. 27 report by Indeed’s Hiring Lab.

Have you been taking your FOBO pills?  Because without a healthy Fear Of Becoming Obsolete, you will likely end up in a dark place, desperately searching for someone to buy what you’re selling. 

After researching 24 sources in seven minutes, ChatGPT came up with the top jobs that might be on the chopping block. 

Microsoft Office wants your employees to use Copilot when filing reports. PixelPose wants them to rely on a headshot generator instead of sitting for a photo shoot. Amazon suggests they write code with the help of its CodeWhisperer tool. And then there’s the ever-present temptation to outsource research and analysis to ChatGPT.

LangChain once held promise as a go-to framework for many developers to build applications powered by LLMs. Even then, it was not perfect and people had a lot of issues. However, a growing number of developers are now moving away from it, citing issues ranging from unnecessary complexity to unstable updates. 

Agents – the AI buzzword of the moment – work autonomously, utilizing external tools to perform complex tasks with far less human direction needed.

Large language models (LLMs) are good at learning from unstructured data. But a lot of the proprietary value that enterprises hold is locked up inside relational databases, spreadsheets, and other structured file types.