2024 was the year of large-scale language models (LLMs), and 2025 looks set to be the year of AI “agents.” These are semi-intelligent systems that leverage LLM to go beyond the usual tricks of generating plausible text and responding to prompts. The idea is that you can give your agent a high-level (or even a vague goal) and break it down into a series of actionable steps. Once you “understand” your goals, you can create a plan to achieve them, just like humans do.
OpenAI Chief Financial Officer Sarah Friar recently explained:
therefore,
financial times: “It could be a researcher, or it could be a useful assistant for the average person or a working mom like me. In 2025, the first highly successful agents to help people with their daily lives will be introduced. It’s like having a digital assistant.
“It doesn’t just react to your instructions; it can learn, adapt, and, perhaps most importantly, take meaningful action to solve problems on your behalf.”
. In other words, Miss Moneypenny on steroids.
So why are these automatic money pennies suddenly being hailed as the next big thing? Even though the tech industry has spent trillions of dollars building huge LLMs, Does it have something to do with the fact that you still can’t expect a reasonable return on your investments? This is not to say that an LLM is useless. This is extremely useful for people whose work involves languages. And for computer programmers, these are very useful. But for many industries, at the moment, they still seem like a solution looking for a problem.
With the advent of AI agents, things could change. LLM has the potential to be attractive as a building block for virtual agents that can efficiently perform many of the complex task sequences that make up the “work” of any organization. Or so the tech industry thinks. And, of course, McKinsey, the consulting giant that provides the subconscious hymn sheet every CEO sings. agent AI,
McKinsey’s Barbles
“we are moving from thinking to acting” as “AI-enabled ‘agents’ that use underlying models to execute complex multi-step workflows across the digital world” are adopted.
If that really happens, we may need to rethink our assumptions about how AI will change the world. At the moment, we are primarily concerned with what technology can do for individuals or humanity (or both). But if McKinsey & Company’s claims are correct, deeper long-term effects could come through the way AI agents transform companies. After all, companies are actually machines for managing complexity and turning information into decisions.
Political scientist Henry Farrell, a keen observer of these issues, suggests this possibility. LLM,
he claims “an engine for summarizing vast amounts of information into something useful.” Because information is the driving force behind their operations, large companies will adopt any technology that provides a more intelligent and contextual way of processing information. information – as opposed to just something data they are currently process. As a result, Farrell says, companies will “introduce LLMs in ways that seem boring and technical, except for things that are immediately relevant, for better or worse, but actually important.” Big organizations shape our lives! As people change, our lives will change in countless seemingly unexciting but important ways.
At one point in his essay, Farrell likens this “boring and technical” transformative impact of LLMs to the way a humble spreadsheet reshapes large organizations. this is,
classy explosion Written by economist and former stock analyst Dan Davis
irresponsible machine It was one of the nicest surprises of the year. He points out that spreadsheets have “enabled entirely new working styles for the financial industry in two ways.” First, it allows for the creation of larger and more detailed financial models, allowing for different ways of budgeting, creating business plans, evaluating investment options, etc. And second, this technology allows for repetitive work. “Instead of thinking about what assumptions make the most business sense and then sitting down and predicting them, Excel [Microsoft’s spreadsheet product] We just presented our predictions and encouraged them to tweak their assumptions up or down until they got an answer they were happy with. What’s more, it’s also an answer that your boss will be satisfied with.
The moral of the story is clear. Spreadsheets were as revolutionary a technology when they first appeared in 1978 as ChatGPT is in 2022. However, it has now become a routine and integral part of organizational life. The emergence of AI “agents” built from models like GPT appears to be following a similar pattern. In turn, the organizations that absorb them will also evolve. And in time, the world may rediscover the famous dictum of Marshall McLuhan’s colleague John Culkin: “We shape our tools, and our tools shape us.”
what i was reading
economics story
transcription of
fascinating interview We will talk about economics, pluralism, and democracy with renowned economist Hajun Chan.
AI?
“False consolation due to AI skepticism”
energetic essay Casey Newton on the two “camps” in the AI debate.
Trump’s next move
“I have a cunning plan…” Here is Charlie Stross’ blog post:
A sketch of a true dystopian story Regarding the impact of President Trump’s inauguration.
Source: www.theguardian.com
