Originally published in MIT News, March 25, 2024
Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.
Large language models, such as those that power popular artificial intelligence chatbots like ChatGPT, are incredibly complex. Even though these models are being used as tools in many areas, such as customer support, code generation, and language translation, scientists still don’t fully grasp how they work.
They found a surprising result: Large language models (LLMs) often use a very simple linear function to recover and decode stored facts. Moreover, the model uses the same decoding function for similar types of facts. Linear functions, equations with only two variables and no exponents, capture the straightforward, straight-line relationship between two variables.
The researchers showed that, by identifying linear functions for different facts, they can probe the model to see what it knows about new subjects, and where within the model that knowledge is stored.
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Researchers demonstrate a technique that can be used to probe a model to see New York Knicks OVO Varsity Jacket
By identifying these linear functions, scientists can probe LLMs to understand Pokerogue what they know about new subjects and pinpoint where this knowledge is stored, shedding light on the inner workings of these complex AI systems.
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LLMs are trained on massive datasets that include a wide range of text from books, articles, websites, and other fnf sources. During training, the model learns patterns, structures, and facts from this data.
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Researchers have discovered that large language models (LLMs), like those used in AI chatbots, often utilize simple linear functions to decode and retrieve stored information. This surprising finding reveals that these models use the same decoding function for similar types of facts. Invisalign Doctor Site
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It’s amazing to think about how LLMs can encode information, maybe in future we’ll have some kind of hex editor to browser their “mind”. Xeno Executor
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This is actually pretty cool! I always wondered how these LLMs managed to pull information—linear functions, huh? That’s simpler than I expected! Makes you wonder what else we don’t know about how they work. If you’re curious about other cutting-edge AI projects, take a look at Lanta AI.
Wow, it’s wild how something as complex as an LLM can use such a simple trick—just a linear function—to pull out facts it “remembers.” Makes you wonder what other secrets are hiding in plain sight inside these models. By the way, if you ever want to take a break and play a quirky game, check out bad ice cream—it’s my go-to for some quick fun!
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It’s impressive how this research reveals how large language models can retrieve knowledge in a simple yet efficient way! level devil
In a new study, researchers have found a way to probe large language models (LLMs) to see what they know about new topics. They discovered that these complex models surprisingly use simple linear functions. wisely by adp