What Is GenAI? | Intel
Summary
TLDRThe video script delves into the evolution of AI, highlighting the shift from analytical AI to large language models capable of processing both structured and unstructured data. It emphasizes the models' ability to anticipate word sequences and generate content like poems in various styles, showcasing the potential for creative expression and learning. The script also underscores the importance of human interaction, where users prompt AI to generate customized content, maintaining control over the creative process.
Takeaways
- π§ AI has evolved from analytical to large language models that can process both structured and unstructured data.
- π Large language models are capable of handling data from various sources, including the internet, Reddit, and Google Search.
- π These models can quickly process and understand unstructured data, which was previously difficult to organize and model.
- π They have learned to anticipate the next word in a sequence with high accuracy, like 'dogs' following 'cats and' in the phrase 'it's raining cats and dogs'.
- π€ The models can sometimes make mistakes, which is referred to as 'hallucination', but this is part of the core model's learning process.
- π¬ Humans interact with AI through prompts, asking questions and giving instructions to generate content or perform tasks.
- π AI can assist in creative tasks, such as writing a poem, and can modify the content based on user prompts, like making it shorter or in a different style.
- π¨ Users can experiment with different expressions of ideas using AI, such as translating a poem into Shakespearean English or converting it into a haiku.
- π₯ The user remains in control, deciding which version of the content to share or use, despite AI's assistance in generating options.
- π The advancements in AI represent a significant shift in how we interact with technology, offering new possibilities for creativity and data processing.
Q & A
What is the main difference between traditional AI and the new generation of AI models discussed in the transcript?
-Traditional AI is analytical and requires structured, tagged data to function effectively. The new generation of AI models, however, can process both structured and unstructured data, including information from the internet, making them more versatile and capable of handling a broader range of tasks.
What does the transcript suggest is the first 'cool' thing about large language models?
-The first 'cool' thing is that large language models can take in and process both structured and unstructured data from various sources like the internet, Reddit, and Google Search, which was difficult to organize and model in the past.
How do large language models anticipate the next word in a sequence?
-Large language models are trained on vast amounts of data, allowing them to predict the most likely next word in a sequence with high accuracy. They have learned patterns and associations between words, such as recognizing that 'cats and dogs' is a common phrase, not 'cats and birds'.
What is the potential issue with large language models when they predict the next word incorrectly?
-When large language models predict the next word incorrectly, they may 'hallucinate' or generate incorrect or nonsensical text. This can occur despite their advanced capabilities and training.
How do humans interface with large language models according to the transcript?
-Humans interface with large language models by giving them prompts or questions. This can include requests to write a poem, summarize text, or even translate into different styles of language, such as Shakespearean English or haiku.
What is the role of the user when interacting with a large language model?
-The user is in the driver's seat, asking questions and deciding what they want the AI to do, such as writing a poem or summarizing text. The AI then generates content based on the user's prompts.
Why might a high school student want to use a large language model to write a poem?
-A high school student might use a large language model to experiment with different ways of expressing an idea, to prototype their writing, or to make their text shorter or longer as needed for assignments or personal projects.
How does the transcript describe the process of training large language models?
-The transcript describes the training process as one where the models learn patterns and associations over time, enabling them to predict the most likely next word in a sequence with a high degree of accuracy.
What is the significance of the phrase 'it's raining cats and dogs' in the context of the transcript?
-The phrase 'it's raining cats and dogs' is used as an example to illustrate how large language models can predict and understand the context and sequence of words, knowing that 'dogs' is the correct word to follow 'cats' in this idiomatic expression.
How does the transcript differentiate between the capabilities of AI 40 years ago and the capabilities of AI today?
-The transcript highlights that while AI has been around for 40 years, the new capabilities of AI today involve processing unstructured data and predicting sequences of words, which were not possible with the more analytical AI of the past.
What is the importance of being able to process unstructured data in the context of AI advancements?
-The ability to process unstructured data is crucial because it allows AI to handle a wider variety of information sources, such as the internet, social media, and search results, which are often unstructured and in large volumes.
Outlines
π€ Introduction to Advanced AI Capabilities
This paragraph introduces the evolution of AI, distinguishing between traditional analytical AI and the new capabilities of large language models. It explains that while AI has been around for decades, the breakthrough lies in the ability of these models to process both structured and unstructured data, including content from the internet like Reddit and Google Search. This capability allows for the organization of previously unmanageable data and information, marking a significant advancement in AI technology.
Mindmap
Keywords
π‘AI (Artificial Intelligence)
π‘Analytical AI
π‘Large Language Models
π‘Unstructured Data
π‘Anticipating Sequence
π‘Training
π‘Word Hallucination
π‘Prompts
π‘Dialogue
π‘Poem
π‘Shakespeare English
π‘Haiku
Highlights
AI has been evolving for the last 40 years, with a shift from analytical AI to more advanced capabilities.
Traditional AI required tagging and structuring of information, limiting its flexibility.
New AI models can process both structured and unstructured data, including internet content.
Large language models can quickly interpret and organize diverse data sources like Reddit and Google Search.
AI's ability to handle unstructured data is a significant advancement in the field.
AI models are trained to anticipate the next word in a sequence, improving language understanding.
The model's training helps it predict the most likely next word with high accuracy.
AI can sometimes 'hallucinate' or make mistakes in word prediction.
Human interaction with AI involves giving prompts to guide its responses.
Users can engage in dialogue with AI, asking it to perform tasks like writing a poem.
AI can manipulate text based on user requests, such as shortening or translating into different styles.
AI assists in prototyping and experimenting with different expressions of ideas.
Users maintain control over the AI's output by deciding which version to share.
AI's ability to adapt to various writing styles, such as Shakespearean English or haiku, is notable.
The transcript discusses the practical applications of AI in creative writing and educational settings.
AI's role in helping students explore different ways to express ideas is highlighted.
The importance of the user being in the driver's seat when interacting with AI is emphasized.
Transcripts
but I'm GNA break and just go back to
the basics for just a second of how does
geni actually work and what can it do
that's new and different from other AI
that exists
already AI has been in the works for the
last 40 years AI is is not new but
what's new is prior to this it was
something that we thought of as
analytical Ai and so for every piece of
information you would have to tag it
it's very structured and then when we
put it in a structure where we able to
do amazing things with data the really
cool thing is that these large language
models are able to take structured and
unstructured data which means that it is
able to take everything in the internet
as it's described things on Reddit
things on Google Search and it's able to
very quickly process that information so
that in of itself is like the first
thing that's pretty cool it's able to
get to unstructured data and information
and images and things that were very
difficult for us to be able to organize
and put into a model so that's the first
thing um the the second thing is what
it's doing is it's anticipating what is
the very next so if I have a phrase and
that's a training that it goes through
so if I have a phrase it's raining cats
and we all know that the phrase is it's
raining cats and dogs and what the large
language models have been trained on is
over time they've learned that it's not
raining cats and cats it's is not
raining cats and birds it's raining cats
and dogs and they know that dog is the
most likely next word it's not saying
that I predict that the phrase is it's
rainning cats and dogs with a 99%
probability it's saying that knowing the
sequence of the
words and being trained on the on what
to expect that it's likely that the next
word will be that technology or that
capability is pretty amazing it also can
make some mistakes and we've seen a lot
of cases where it can the word would be
hallucinate but that's the kind of the
core model piece of it and then what we
talked about earlier is how we as humans
interface with it and we give it prompts
and prompts our question and we say and
you can have a dialogue you can say help
me take these words and write a poem
about this now let me see what that poem
would be like 50% shorter let me see if
I wrote that poem in Shakespeare English
what that would be let me see what that
would be like if it were a haiku and the
reason that you'd want to do this is
maybe as the high school student you
want to play with different ways to
express an idea and the idea that you
could have
technology help you with that and
prototype things and make things shorter
and longer but by the way in all of
those cases you're still in the driver's
seat because you're asking the question
and you're deciding what you want to
push forward as the thing that you share
as your poem of choice
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