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Generative AI in a Nutshell - how to survive and thrive in the age of AI — Transcript

by Henrik Kniberg · 3,487 words · 512 segments · language en · Watch on YouTube

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0:00[Music]
0:05ever since computers were invented
0:07they've really just been glorified
0:08calculators machines that execute the
0:11exact instructions given to them by the
0:13programmers but something incredible is
0:15happening now computers have started
0:16gaining the ability to learn and think
0:19and communicate just like we do they can
0:21do creative intellectual work that
0:23previously only humans could do we call
0:25this technology generative Ai and you
0:27may have encountered it already through
0:29products like GPT basically intelligence
0:32is now available as a service kind of
0:34like a giant brain floating in the sky
0:36that anyone can talk to it's not perfect
0:39but it is surprisingly capable and it is
0:40improving at an exponential rate this is
0:43a big deal it's going to affect just
0:45about every person and Company on the
0:47planet positively or negatively this
0:49video is here to help you understand
0:51what generative AI is all about in
0:53Practical terms beyond the hype the
0:54better you understand this technology as
0:56a person team or company the better
0:58equipped you will be to survive and
1:00thrive in the age of AI so here's a
1:03silly but useful mental model for this
1:05you have Einstein in your basement in
1:07fact everyone does and by Einstein I
1:10really mean the combination of every
1:12smart person who ever lived you can talk
1:14to Einstein whenever you want he has
1:16instant access to the sum of all human
1:18knowledge and will answer anything you
1:20want within seconds never running out of
1:21patience he can also take on any role
1:23you want a comedian poet doctor coach
1:27and will be an expert within that field
1:29he has has some humanlike limitations
1:31though he can make mistakes he can jump
1:33to conclusions he can misunderstand you
1:35but the biggest limitation is actually
1:37your imagination and your ability to
1:39communicate effectively with them this
1:41skill is known as prompt engineering and
1:43in the age of AI this is as essential as
1:46reading and writing most people vastly
1:49underestimate what this Einstein in your
1:51basement can do it's like going to the
1:53real Einstein and asking him to proof
1:55read a high school report or hiring a
1:56world-class five-star chef and having
1:59him chop onion the more you interact
2:01with Einstein the more you will discover
2:02surprising and Powerful ways for him to
2:05help you or your company okay enough
2:07fluffy metaphors let's clarify some
2:08terms AI as you probably know stands for
2:11artificial intelligence AI is not new
2:14Fields like machine learning and
2:15computer vision have been around for
2:17decades whenever you see a YouTube
2:18recommendation or a web search result or
2:21whenever you get a credit card
2:22transaction approved that's traditional
2:24AI in action generative AI is AI that
2:27generates new original content rather
2:29than just finding or classifying
2:31existing content that's the G in GPT for
2:33example large language models or llms
2:36are a type of generative AI that can
2:38communicate using normal human language
2:41chat GPT is a product by the company
2:43open AI it started as an llm essentially
2:46an advanced chatbot using a new
2:47architecture called the Transformer
2:49architecture which by the way is the T
2:51in GPT it is so fluent at human language
2:54that anyone can use it you don't need to
2:55be an AI expert or programmer and that's
2:57kind of what triggered the whole
2:58Revolution so how does it actually work
3:02well a large language model is an
3:03artificial neural network basically a
3:06bunch of numbers or or parameters
3:08connected to each other similar to how
3:09our brain is a bunch of neurons or brain
3:11cells connected to each other neural
3:12networks only deal with numbers you send
3:15in numbers and depending on how the
3:16parameters are set all the numbers come
3:18out but any kind of content such as text
3:20or images can be represented as numbers
3:22so let's say I write dogs are when I
3:25send that to a large language model that
3:27gets converted to numbers processed by
3:29the neural network and then the
3:30resulting numbers are converted back
3:31into text in this case the word animals
3:34dogs are animals so yeah this is
3:36basically a guest toex word machine the
3:39interesting part is if we take that
3:40output and combine it with the input and
3:43send it through the model again then it
3:45will continue adding new words that's
3:46what's going on behind the scenes when
3:48you type something in chat GPT in this
3:50case for example it generated a whole
3:51story and I can continue this
3:53indefinitely by adding more prompts a
3:56large language model may have billions
3:58or even trillions of parameters that's
4:00why they're called large so how are all
4:02these numbers set well not through
4:04manual programming that would be
4:06impossible but through training just
4:09like babies learning to speak a baby
4:11isn't told how to speak she doesn't get
4:13an instruction manual instead she
4:15listens to people speaking around her
4:16and when she's heard enough she starts
4:18seeing the pattern she speaks a few
4:20words at first to the Delight of her
4:21parents and then later on full sentences
4:24similarly during a training period the
4:26language model is fed a mindboggling
4:28amount of text to learn from Mostly from
4:31internet sources it then plays guess the
4:33next word with all of this over and over
4:35again and the parameters are
4:37automatically tweaked until it starts
4:38getting really good at predicting the
4:40next word this is called back
4:41propagation which is a fancy term for oh
4:44I guessed wrong I better change
4:45something however to become truly useful
4:47a model also needs to undergo human
4:49training this is called reinforcement
4:51learning with human feedback and it
4:53involves thousands of hours of humans
4:55painstakingly testing and evaluating
4:57output from the model and giving
4:58feedback kind of like training a a dog
5:01with a clicker to reinforce good
5:02behavior that's why a model like GPT
5:04won't tell you how to rob a bank it
5:06knows very well how to rob a bank but
5:08through human training it has learned
5:09that it shouldn't help people commit
5:11crimes when training is done the model
5:13is mostly Frozen other than some fine
5:15tuning that can happen later that's what
5:17the P stands for in GPT pre-trained
5:19although in the future we will probably
5:20have models that can learn continuously
5:22rather than just uh during training and
5:24fine-tuning now although chat GPT kind
5:26of got the ball rolling GPT isn't the
5:29only model out there in fact new models
5:31are sprouting like mushrooms they vary a
5:34lot in terms of speed capability and
5:36cost some can be downloaded and run
5:37locally others are only online some are
5:40free or open source others are
5:41commercial products some are super easy
5:43to use While others require complicated
5:46technical setup some are specialized for
5:48certain use cases others are more
5:50General and can be used for almost
5:52anything and some are baked into
5:54products in the form of co-pilots or or
5:56chat windows it's it's the Wild West
6:00just keep in mind that you generally get
6:01what you pay for so with a free model
6:04you may just be getting a smart high
6:06school student in your basement rather
6:08than Einstein the difference between for
6:11example GPT 3.5 and gp4 is
6:14massive note that there are different
6:16types of generative AI models that
6:18generate different types of content
6:20textto text models like gpc4 take text
6:23as input and generate text as output the
6:25text can be natural language but it can
6:26also be structured information like code
6:29Json or HTML I use this a lot myself to
6:32generate code when programming uh it
6:33saves an incredible amount of time and I
6:35also learn a lot from the code it
6:37generates text to image models will
6:38generate images describe what you want
6:40and an image gets generated for you you
6:42can even pick a style image to image
6:45models can do things like transforming
6:47or combining images and we have image to
6:50text models which describe the contents
6:52of a given image and speech to text
6:54models create voice transcriptions which
6:56is useful for things like uh meeting
6:58notes text to audio models they generate
7:00music or sounds from a prompt for
7:02example here is some sound generated
7:04from The Prompt people talking in a
7:08busy okay guys enough stop now thank you
7:13and there are even text to video models
7:15that generate videos from a prompt
7:17sooner or later we'll have infinite
7:18movie series that autogenerate the next
7:20episode tailored to your tastes as
7:22you're watching kind of scary if you
7:24think about it one Trend now is
7:26multimodal AI products meaning they
7:28combine different models into one
7:30product so you can work with text images
7:32audio Etc without switching tools the
7:35chat GPT mobile app is a good example of
7:37this just for fun I took a photo of this
7:40room and I asked where I could hide
7:41stuff I kind of like that it mentioned
7:44the stove but warned that that it could
7:46get hot there when I have things to
7:48figure out such as the contents of this
7:50video I like to take walks using chat
7:52GPT as as a sounding board I start by
7:55saying always respond with the word okay
7:57unless I ask you for something that way
7:59it'll just listen and not interrupt
8:01after I finish dumping my thoughts I ask
8:03for feedback we have some discussion and
8:06then I ask it to summarize and text
8:07afterwards I really recommend trying
8:09this it's it's a really useful way to
8:11use tools like this turns out Einstein
8:13isn't stuck in the basement after all
8:15you can take him out for a walk
8:17initially language models were just word
8:19predictors statistical machines with
8:22limited practical use but as they became
8:24larger and were trained on more data
8:26they started gaining emergent
8:28capabilities unexpect capabilities that
8:30surprised even the developers of the
8:31technology they could role playay write
8:34poetry write highquality code discuss
8:36company strategy provide legal and
8:38medical advice coach teach basically
8:41creative and intellectual things that
8:43only humans could do previously it turns
8:46out that when a model has seen enough
8:47text and images it starts to see
8:49patterns and understand higher level
8:51Concepts just like a baby learning to
8:53understand the world let's take a simple
8:55example I'll give gp4 this little
8:57drawing that involves a string a pair of
9:00scissors an egg a pot and a fire what
9:03will happen if I use the scissors the
9:05model has most likely not been trained
9:07on this exact scenario yet it gave a
9:10pretty good answer which demonstrates a
9:11basic understanding of the nature of
9:13scissors eggs gravity and heat when gp4
9:16was released I started using it as a
9:18coding assistant and I was blown away
9:20when prompted effectively it was a
9:22better programmer than anyone I've
9:23worked with same with article writing
9:25product design Workshop planning and
9:27just about anything I used it for
9:29the main bottleneck was my prompt
9:32engineering skills so I decided to make
9:33a career shift and focus entirely on
9:35learning and teaching how to make this
9:37technology useful hence this video now
9:40let's take a step back and look at the
9:41implications for 300,000 years or so we
9:44homosapiens have been the most
9:46intelligent species on Earth depending
9:48of course on how you define intelligence
9:50but the thing is our intellectual
9:51capabilities aren't really improving
9:53that much our brains are about the same
9:55size same weight as they've been for
9:56thousands of years computers on the
9:58other hand have been around for only 80
10:00years or so and now with generative AI
10:02they are suddenly capable of speaking
10:04human languages fluently and carrying
10:06out an increasing number of intellectual
10:08creative tasks that previously only
10:10humans could do so we are right here at
10:12the Crossing Point where AI is better at
10:14some things and humans are better at
10:15some things but ai's capabilities are
10:17improving at an exponential rate while
10:19ours aren't we don't know how long that
10:22exponential Improvement will continue or
10:24if it will level off at some point but
10:25we're definitely entering a new world
10:27order now this isn't the first re
10:29Revolution we've experienced we tamed
10:31fire we learned how to do agriculture we
10:33invented the printing press steam power
10:35Telegraph these were all revolutionary
10:37changes but they took decades or
10:39centuries to become widespread in the AI
10:42Revolution new technology spreads
10:44worldwide almost instantly dealing with
10:46this rate of change is a huge challenge
10:48for both individuals and
10:50companies I've noticed that people and
10:52companies tend to fall into different
10:54kind of mindset categories when it comes
10:56to AI on one side we have denial the
10:59belief that AI cannot do my job or we
11:02don't have time to look into this
11:03technology this is a dangerous place to
11:05be a common saying is AI might not take
11:08your job but people using AI will and
11:11this is true for both individuals and
11:13companies on the other side of the scale
11:15we have panic and despair the belief
11:16that AI is going to take my job no
11:18matter what AI is going to make my
11:19company go bankrupt neither of these
11:21mindsets are helpful so I propose a
11:24middle ground a balanced positive
11:26mindset AI is going to make me my team
11:28my company insanely productive
11:31personally with this mindset I feel like
11:33I've gained superpowers I can go from
11:35idea to result in so much shorter time I
11:38can focus more on what I want to achieve
11:40and less on the grunt work of building
11:41things and I'm learning a lot faster too
11:43it's like having an awesome Mentor with
11:45me at all times this mindset not only
11:47feels good but it also equips you for
11:49the future makes you less likely to lose
11:51your job or your company and more likely
11:53to thrive in the age of AI despite all
11:55the
11:56uncertainty so one important question is
11:59is human role X needed in the age of AI
12:02for example are doctors needed
12:03developers lawyers CEOs uh whatever so
12:06this question becomes more and more
12:08relevant as the AI capabilities improve
12:11well some jobs will disappear for sure
12:13but for most roles I think we humans are
12:15still needed someone with domain
12:17knowledge still needs to decide what to
12:19ask the AI how to formulate The Prompt
12:21what context needs to be provided and
12:23how to evaluate the result AI models
12:25aren't perfect they can be absolutely
12:27brilliant sometimes but sometimes also
12:30terribly stupid they can sometimes
12:32hallucinate and provide bogus
12:33information in a very convincing way so
12:36when should you trust AI response when
12:38should you double check or do the work
12:40yourself what about legal compliance
12:42data security what information can we
12:44send to an AI model and where is that
12:46data stored a human expert is needed to
12:49make these judgment calls and compensate
12:51for the weaknesses of the AI model so I
12:53recommend thinking of AI as your
12:55colleague a genius but also an oddball
12:57with some personal quirks that you need
12:59to learn to work with you need to
13:00recognize when your Genius colleague is
13:02drunk as a doctor my AI colleague can
13:05help diagnose rare diseases that I
13:06didn't even know existed as a lawyer my
13:09AI colleague could do legal research and
13:11review contracts allowing me to spend
13:12more time with my client or as a teacher
13:15my AI colleague could grade tests help
13:18generate course content provide
13:19individual support to students Etc and
13:22if you're not sure how I can help you
13:24just ask it I work as X how can you help
13:27me overall I find that that the
13:29combination of human plus AI That's
13:31where the magic lies it's important to
13:34distinguish between the models and the
13:36products that build on top of them as a
13:38user you don't normally interact with
13:39the model directly instead you interact
13:42with a product website or a mobile app
13:43which in turn talks to the model behind
13:45the scenes products provide a user
13:47interface and add capabilities and data
13:49that aren't part of the model itself for
13:51example the chat GPT product keeps track
13:54of your message history while the GPT 4
13:56model itself doesn't have any message
13:58history as a developer you can use these
14:01models to build your own AI powered
14:02products and features for example let's
14:05say you have an e-learning site you
14:06could add a chat bot to answer questions
14:08about the courses or as a recruitment
14:10company you might build AI powered tools
14:12to help evaluate candidates in both
14:14these cases your users interact with
14:16your product and then your product
14:18interacts with the model this is done
14:19via apis or application programming
14:21interfaces which allow your code to talk
14:23to the model so here's a simple example
14:26of using open AI API to talk to GPT not
14:29a lot of code needed and here's another
14:31example of the automatic candidate
14:33evaluation thing I talked about it takes
14:35a job description and a bunch of CVS in
14:37a folder and evaluates each candidate
14:40automatically and incidentally the code
14:42itself is mostly AI written as a product
14:45developer you can use AI models kind of
14:48like an external brain to insert
14:50intelligence into your product very
14:52powerful in order to use generative AI
14:55effectively you need to get good at
14:57prompt engineering or prompt design as I
14:59prefer to call it this skill is needed
15:01both as a user and as a product
15:03developer because in both cases you need
15:05to be able to craft effective prompts
15:07that produce useful results from an AI
15:09model here's an example let's say I want
15:11help planning a workshop this prompt is
15:14unlikely to give useful results because
15:16no matter how smart the AI is if it
15:18doesn't know the context of my workshop
15:20it can only give fague high level
15:22recommendations the second prompt is
15:24better now I provided some context this
15:26is normally done iteratively write a
15:28prompt look at the result add a
15:30follow-up prompt to provide more
15:31information or edit the original prompt
15:34and rinse and repeat until you get a
15:35good result in this third approach I ask
15:38it to interview me so instead of me
15:40providing a bunch of context up front
15:42I'm basically saying what do you need to
15:43know in order order to help me and then
15:45it will propose a workshop agenda after
15:47I often combine these two I provide a
15:49bit of context and then I tell it to ask
15:51me if it needs any more information
15:53these are just some examples of prompt
15:54engineering techniques so overall the
15:57better you get at prompt engineering the
15:59faster and better results you will get
16:00from AI there are plenty of courses
16:02books videos articles to help you learn
16:04this but the most important thing is is
16:06to practice and Learn by doing a nice
16:08side effect is that you will become
16:09better at communicating in general since
16:11prompt engineering is really all about
16:13Clarity and effective
16:15communication I think the next Frontier
16:17for generative AI is autonomous agents
16:19with tools these are AI powerered
16:21software entities that run on their own
16:23rather than just sitting around waiting
16:24for you to prompt them all the time so
16:26you go down to Einstein in your basement
16:28and do what a good good leader would do
16:29for a team you give him a high level
16:31Mission and the tools needed to
16:32accomplish it and then open the door and
16:34let him out to run his own show without
16:36micromanagement the tools could be
16:38things like access to the internet
16:40access to money ability to send and
16:42receive messages order pizza or whatever
16:45for this prompt engineering becomes even
16:47more important because your autonomous
16:49tool wielding agent can do a lot of good
16:51or a lot of harm depending on how well
16:54you craft that mission
16:55statement all right let's wrap it up
16:58here are the key things I hope you will
17:00remember from this video generative AI
17:02is a super useful tool that can help
17:04both you your team and your company in a
17:06big way the better you understand it the
17:08more likely it is to be an opportunity
17:10rather than a threat generative AI is
17:12more powerful than you think the biggest
17:14limitation is not the technology but
17:17your imagination like what can I do and
17:19your prompt engineering skills how do I
17:21do it prompt engineeringdesign is a
17:24crucial skill like all new skills just
17:27accept that you will kind of suck at at
17:29first but you'll improve over time with
17:31deliberate practice so my best tip is
17:34experiment make this part of your
17:36day-to-day life and the Learning Happens
17:38automatically hope this video was
17:40helpful thanks for watching
17:44[Music]

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