But as vast amounts of data are fed into the terminal – not just earnings and asset prices, but also weather forecasts, shipping logs, factory locations, consumer spending patterns, personal loans, and so on – valuable information is being lost. “It’s become more and more volatile,” says Shawn Edwards, Bloomberg’s chief technology officer. “You miss things, or it takes a lot of time.”
To address the problem, Bloomberg is testing a chatbot-style interface for the terminal, ASKB (pronounced ask-bee), built on top of a basket of different language models. The broader idea is to help finance professionals condense labor-intensive tasks, and make it possible to test abstract investment theses against data through natural language prompts.
At the time of publishing, the ASKB beta is open to about a third of the software’s 375,000 users; Bloomberg has not specified a date for a full release.
WIRED spoke to Edwards at Bloomberg’s luxurious London headquarters in early April. We discussed the incentives to redesign the terminal, whether conservatives might shy away from change, and Bloomberg’s efforts to address hallucinations.
The following conversation has been edited for length and clarity.
Wired: Shawn, tell me about the rationale for this overhaul of the terminal.
Shawn Edwards: Over the years, Bloomberg has been adding to this extensive dataset that we have. Often, finding the right piece of data in a sea of information is the deciding factor in whether you are successful or not. It’s become more unstable: you forget things, or it takes too long.
The primary problem we are solving with generative AI is helping users find key insights and synthesize a view of the world around a particular idea.
The concept is that unused alpha is hidden somewhere in the data, and ASKB will help uncover it?
Yes. The user gets to ask higher-level questions—the thesis they have in mind—instead of asking about particular data points. ‘What impact are the war in Iran and changes in oil prices going to have on my portfolio?’ This is a big, big question with many dimensions. Can we synthesize that answer in minutes?
In a scenario where everyone is able to navigate the confusion of data, what will separate the mediocre traders from the best traders?
These tools are not magical. they don’t make any average [employee] Suddenly great. The difference will be your thoughts.
In the hands of experts, it allows them to do better analysis, deeper research – filtering out 10 great ideas when they might have only had time for one. If you’re a mediocre analyst, those will be 10 mediocre ideas.
Bloomberg has introduced ASKB as a form of agentic AI. At first glance, it looks more like a chatbot interface than something that essentially automates tasks. What is agentic about ASKB?
There is income that comes every quarter. My job as an analyst is to be prepared for what might happen in that earnings call. Whatever company I’m preparing for, I’m looking at how their value compares to their peers, searching through a lot of documents, looking at their fundamentals, and so on. In the earning season, I am not sleeping.
With ASKB, I can create workflow templates. I can write a long query, and say, ‘Hey, here’s all the data I’ll need.’ Give me a summary of the bullish and bearish cases, what the Street is saying, what the guidance is. Now, I want to schedule [the workflows] Or trigger them when I see this or that situation in the world.
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