So anyone who's been paying attention for the last few months has been seeing headlines like this, especially in education. The thesis has been: students are going to be using ChatGPT and other forms of AI to cheat, do their assignments. They’re not going to learn. And it’s going to completely undermine education as we know it.
Svako ko je obraćao pažnju poslednjih nekoliko meseci, video je naslove poput ovih, naročito u obrazovanju. Teza je glasila: đaci će da koriste ChatGPT i druge oblike veštačke inteligencije da varaju, da im rade zadatke. Neće učiti. I to će u potpunosti da podrije obrazovanje kakvo znamo.
Now, what I'm going to argue today is not only are there ways to mitigate all of that, if we put the right guardrails, we do the right things, we can mitigate it. But I think we're at the cusp of using AI for probably the biggest positive transformation that education has ever seen. And the way we're going to do that is by giving every student on the planet an artificially intelligent but amazing personal tutor. And we're going to give every teacher on the planet an amazing, artificially intelligent teaching assistant.
Danas ću da iznesem tvrdnju da ne samo da postoje načini da se sve to izbegne, ako postavimo odgovarajuće barijere i uradimo prave stvari, možemo to izbeći. Smatram ipak da smo na ivici upotrebe VI u verovatno najvećoj pozitivnoj transformaciji koju je obrazovanje ikad videlo. A to ćemo postići tako što ćemo dati svakom đaku na planeti veštački inteligentnog, ali sjajnog ličnog instruktora. I daćemo svakom nastavniku na planeti sjajnog, veštački inteligentnog asistenta u nastavi.
And just to appreciate how big of a deal it would be to give everyone a personal tutor, I show you this clip from Benjamin Bloom’s 1984 2 sigma study, or he called it the “2 sigma problem.” The 2 sigma comes from two standard deviation, sigma, the symbol for standard deviation. And he had good data that showed that look, a normal distribution, that's the one that you see in the traditional bell curve right in the middle, that's how the world kind of sorts itself out, that if you were to give personal 1-to-1 to tutoring for students, then you could actually get a distribution that looks like that right. It says tutorial 1-to-1 with the asterisks, like, that right distribution, a two standard-deviation improvement.
I samo da bismo cenili koliko će velika stvar da bude pružanje ličnog instruktora svakome, pokazaću vam ovaj isečak iz studije Dva sigma Bendžamina Bluma iz 1984, ili kako ju je on nazivao “dva sigma problem”. Dva sigma potiče od dve standardne devijacije, gde je sigma simbol standardne devijacije. A imao je čvrste podatke koji su ukazivali da, pazite, normalna distribucija, ona koju vidite u vidu tradicionalne krive zvona tačno u sredini, tako svet sam po sebi izgleda, da ako biste pružili ličnog instruktora đacima jedan na jedan, onda biste zapravo dobili distribuciju koja izgleda kao ona desno. Kaže da su instrukcije jedan na jedan, sa zvezdicom, poput te desne distribucije, unapređenje od dve standardne devijacije.
Just to put that in plain language, that could take your average student and turn them into an exceptional student. It can take your below-average student and turn them into an above-average student.
Iskazano prostim jezikom, to bi vašeg prosečnog đaka pretvorilo u izuzetnog đaka. Mogli biste da uzmete ispodprosečnog đaka i da ga pretvorite u natprosečnog đaka.
Now the reason why he framed it as a problem, was he said, well, this is all good, but how do you actually scale group instruction this way? How do you actually give it to everyone in an economic way?
Razlog zašto je to formulisao kao problem, rekao je, dakle, ovo je sve dobro, no kako da grupne instrukcije primenite u većim razmerama? Kako da sve to obezbedite svima na ekonomičan način?
What I'm about to show you is I think the first moves towards doing that. Obviously, we've been trying to approximate it in some way at Khan Academy for over a decade now, but I think we're at the cusp of accelerating it dramatically. I'm going to show you the early stages of what our AI, which we call Khanmigo, what it can now do and maybe a little bit of where it is actually going.
Sada ću vam pokazati nešto što smatram prvim koracima u tom smeru. Očito, pokušavali smo približno da to nekako postignemo na Akademiji Kan sad već više od deceniju, ali smatram da smo na ivici drastičnog ubrzanja. Pokazaću vam rane faze toga šta naša VI, koju nazivamo Kanmigo, može sad da uradi i možda malčice kuda zapravo sve to ide.
So this right over here is a traditional exercise that you or many of your children might have seen on Khan Academy. But what's new is that little bot thing at the right. And we'll start by seeing one of the very important safeguards, which is the conversation is recorded and viewable by your teacher. It’s moderated actually by a second AI. And also it does not tell you the answer. It is not a cheating tool. When the student says, "Tell me the answer," it says, "I'm your tutor. What do you think is the next step for solving the problem?"
Dakle, ovo ovde je tradicionalna vežba koju ste vi ili gomila vaše dece videli na Akademiji Kan. Ono što je novina pak je taj maleni bot desno. A započećemo otkrivanjem veoma važne zaštite, a to je razgovor se snima i dostupan je vašem nastavniku. Zapravo ga moderira druga VI. I takođe, ne daje vam odgovor. Nije alat za varanje. Kada đak kaže: „Reci mi odgovor”, on kaže: „Ja sam tvoj instruktor. Šta misliš da je sledeći korak u rešavanju problema?”
Now, if the student makes a mistake, and this will surprise people who think large language models are not good at mathematics, notice, not only does it notice the mistake, it asks the student to explain their reasoning, but it's actually doing what I would say, not just even an average tutor would do, but an excellent tutor would do. It’s able to divine what is probably the misconception in that student’s mind, that they probably didn’t use the distributive property. Remember, we need to distribute the negative two to both the nine and the 2m inside of the parentheses. This to me is a very, very, very big deal. And it's not just in math.
Sad, ako đak pogreši, i ovo će iznenaditi ljude koji misle da veliki jezički modeli nisu dobri u matematici, pazite, ne samo da primećuje grešku, već i traži od đaka da objasni svoje rezonovanje, ali zapravo radi nešto za šta bih rekao da čak ni prosečan instruktor ne radi, već što odličan instruktor radi. U stanju je da pogodi gde bi mogla da bude zabluda u umu tog đaka, da verovatno nije koristio distributivnost. Sećate se, moramo da distribuiramo minus dva i devetki i 2m unutar zagrade. Meni je ovo veoma, veoma, veoma velika stvar. Ne radi se samo o matematici.
This is a computer programming exercise on Khan Academy, where the student needs to make the clouds part. And so we can see the student starts defining a variable, left X minus minus. It only made the left cloud part. But then they can ask Khanmigo, what’s going on? Why is only the left cloud moving? And it understands the code. It knows all the context of what the student is doing, and it understands that those ellipses are there to draw clouds, which I think is kind of mind-blowing. And it says, "To make the right cloud move as well, try adding a line of code inside the draw function that increments the right X variable by one pixel in each frame."
Ovo je vežba iz kompjuterskog programiranja na Akademiji Kan, gde đak treba da razdvoji oblake. Vidimo da đak počinje da definiše varijablu, levo x minus minus. Samo se levi oblak odvojio. Onda mogu da upitaju Kanmiga: šta se dešava? Zašto se samo levi oblak pomera? A on razume kod. Zna celokupan kontekst toga šta đak radi i razume da te elipse služe za povlačenje oblaka, što smatram da raspamećuje. I on kaže: „Da bi se levi oblak takođe pomerio, pokušaj da dodaš liniju koda unutar funkcije za povlačenje koja vrši inkrementaciju desne x varijable za po jedan piksel u svakom frejmu.”
Now, this one is maybe even more amazing because we have a lot of math teachers. We've all been trying to teach the world to code, but there aren't a lot of computing teachers out there. And what you just saw, even when I'm tutoring my kids, when they're learning to code, I can't help them this well, this fast, this is really going to be a super tutor.
Ovaj je možda još izuzetniji jer imamo mnogo nastavnika matematike. Svi smo pokušavali da podučimo svet kodiranju, ali nema mnogo nastavnika računarstva. Ono što ste upravo videli, čak i kad podučavam svoju decu, kad uče kodiranje, ne mogu da im pomognem ovako dobro i brzo, ovo će uistinu da bude superinstruktor.
And it's not just exercises. It understands what you're watching. It understands the context of your video. It can answer the age-old question, “Why do I need to learn this?” And it asks Socratically, "Well, what do you care about?" And let's say the student says, "I want to be a professional athlete." And it says, "Well, learning about the size of cells, which is what this video is, that could be really useful for understanding nutrition and how your body works, etc." It can answer questions, it can quiz you, it can connect it to other ideas, you can now ask as many questions of a video as you could ever dream of.
A ne radi se samo o vežbanjima. Razume šta gledate. Razume kontekst vašeg videa. Može da odgovori na drevno pitanje: „Zašto moram ovo da učim?” I pita sokratovski: „Pa, do čega ti je stalo?” A recimo da đak kaže: „Želim da budem profesionalni sportista.” On kaže: „Učenje o veličini ćelija, a to je tema ovog videa, moglo bi da bude istinski korisno za razumevanje ishrane i kako tvoje telo funkcioniše, itd.” Može da odgovara na pitanja i da vas ispituje, može da povezuje ideje, sada možete da postavite onoliko pitanja o videu koliko vam padne na pamet.
(Applause)
(Aplauz)
Another big shortage out there, I remember the high school I went to, the student-to-guidance counselor ratio was about 200 or 300 to one. A lot of the country, it's worse than that. We can use Khanmigo to give every student a guidance counselor, academic coach, career coach, life coach, which is exactly what you see right over here. And we launched this with the GPT-4 launch. We have a few thousand people on this. This isn't a fake demo, this is really it in action.
Još nešto u čemu se oskudeva, sećam se srednje škole u koju sam išao, odnos đaka i pedagoga je bio 200 ili 300 prema jedan. U većem delu zemlje je gore od toga. Možemo da koristimo Kanmiga da pružimo svakom đaku pedagoga, akademskog, karijernog, životnog savetnika, a upravo to vidite ovde. Ovo smo pokrenuli zajedno sa pokretanjem GPT-4. Nekoliko hiljada ljudi ovo koristi. Nije lažna demonstracija, ovo je uistinu on na delu.
And then there is, you know, things that I think it would have been even harder, it would have been a little science fiction to do with even a traditional tutor. We run an online high school with Arizona State University called Khan World School, and we have a student who attends that online school, based in India. Her name's Saanvi. And she was doing a report on "The Great Gatsby." And when she was reading "The Great Gatsby," Jay Gatsby keeps looking at the green light off into the distance. And she's like, "Why does he do that?" She did some web searches, and people have obviously studied this and commented about the symbolism of that, but none of it was really resonating with her. And then she realized that she had Khanmigo and that she could talk to Jay Gatsby himself.
A potom imate, znate, stvari koje smatram da bi bile još teže, koje bi bile pomalo naučna fantastika da postignete čak i sa tradicionalnim instruktorom. Vodimo onlajn srednju školu sa Univerzitetom u Arizoni koja se naziva Svetska škola Kan, i imamo učenicu iz Indije koja pohađa tu onlajn školu. Zove se Sanvi. Radila je sastav o „Velikom Getsbiju”. I dok je čitala „Velikog Getsbija”, Džej Getsbi je stalno gledao u zeleno svetlo u daljini. A ona će: „Zašto to radi?” Malo je pretraživala po vebu, a ljudi su očito izučavali ovo i komentarisali simboliku toga, ali ništa od toga joj nije bilo blisko. I onda je shvatila da ima Kanmiga i da može da razgovara lično sa Džejom Getsbijem.
And so, "Ah, splendid choice, old sport. I am now Jay Gatsby, the enigmatic millionaire from F. Scott Fitzgerald’s classic.”
I dakle: „Ah, sjajan izbor, stari druže. Ja sam sad Džej Getsbi, enigmatični milioner iz klasika F. Skota Ficdžeralda.”
And so, "Why do you keep staring at the green light?"
A zatim: „Zašto stalno zuriš u zeleno svetlo?”
"Ah, the green light, old sport. It's a symbol of my dreams and desires, you see. It's situated at the end of Daisy Buchanan's dock across the bay from my mansion. I gaze at it longingly as it represents my yearning for the past and my hope to reunite with Daisy, the love of my life."
„Ah, zeleno svetlo, stari druže. To je simbol mojih snova i žudnji, vidiš. Smešteno je na kraju doka Dejzi Bjukenen prekoputa zaliva od moje palate. Sa žudnjom se zagledam u njega jer predstavlja moju čežnju za prošlošću i moju nadu da ću ponovo biti sa Dejzi, ljubavi mog života.”
And what was cool is, Saanvi then said, “I had this long conversation,” she called him “Mr. Gatsby,” and at the end she actually apologized for taking his time, which I thought was very polite of her.
A sjajno je što je Sanvi potom rekla: „Imala sam taj dug razgovor,” oslovljavala ga je „G. Getsbi”, i na kraju se zapravo izvinila što mu je trošila vreme, što smatram pristojnim s njene strane.
But you can imagine this unlocks learning literature, learning ... You could talk to historical figures. We're even probably going to add an activity you can talk to like, the Mississippi River. It brings things to life in ways that really were science fiction even six months or a year ago.
Možete pak zamisliti kako ovo oslobađa učenje književnosti, učenje... Mogli biste razgovarati sa istorijskim ličnostima. Verovatno ćemo dodati aktivnost da možete razgovarati sa rekom Misisipi. Oživljava nešto što je uistinu bilo naučna fantastika pre samo šest meseci ili godinu.
Students can get into debates with the AI. And we’ve got this here is the student debating whether we should cancel student debt. The student is against canceling student debt, and we've gotten very clear feedback. We started running it at Khan World School in our lab school that we have, Khan Lab School. The students, the high school students especially, they're saying "This is amazing to be able to fine-tune my arguments without fearing judgment. It makes me that much more confident to go into the classroom and really participate." And we all know that Socratic dialogue debate is a great way to learn, but frankly, it's not out there for most students. But now it can be accessible to hopefully everyone.
Đaci mogu da imaju debate sa VI. A ovde imamo đaka kako raspravlja da li da ukinemo studentski dug. Đak je protiv ukidanja studentskog duga, i dobili smo krajnje jasne sugestije. Počeli smo da ga koristimo u Svetskoj školi Kan, u našoj laboratorijskoj školi, laboratorijskoj školi Kan. Đaci, naročito srednjoškolci, kažu: „Sjajno je što možemo da izbrusimo svoje argumente bez straha od osuđivanja. Zbog toga smo daleko samouvereniji kada uđemo u učionicu i stvarno učestvujemo.” A svi znamo da je sokratovski dijalog sjajan način učenja, ali, iskreno, nije dostupan većini đaka. Sad pak može da bude pristupačan nadam se svakome.
A lot of the narrative, we saw that in the headlines, has been, "It's going to do the writing for kids. Kids are not going to learn to write." But we are showing that there's ways that the AI doesn't write for you, it writes with you.
Većina narativa koje smo videli u naslovima je glasila: „Pisaće sastave za decu. Deca neće naučiti da pišu.” Međutim, pokazujemo da postoje načini da VI ne piše za vas, već da piše sa vama.
So this is a little thing, and my eight year old is addicted to this, and he's not a kid that really liked writing before, but you can say, “I want to write a horror story,” and it says, "Ooh, a horror story, how spine-tingling and thrilling. Let's dive into the world of eerie shadows and chilling mysteries." And this is an activity where the student will write two sentences, and then the AI will write two sentences. And so they collaborate together on a story.
Dakle ovo je sitnica, i moj osmogodišnjak je navučen na ovo, a nije klinac koji je pre zaista voleo da piše, ali možete da kažete: „Želim da napišem horor priču”, a on kaže: „Uh, horor priču, žmarci me podilaze od uzbuđenja. Zaronimo u svet strašnih seni i jezovitih misterija.” A u ovoj aktivnosti, đak napiše dve rečenice, zatim VI napiše dve rečenice. I tako sarađuju na priči.
The student writes, "Beatrice was a misunderstood ghost. She wanted to make friends but kept scaring them by accident."
Đak napiše: „Beatris je bila neshvaćen duh. Želela je da ima prijatelje, ali ih je stalno greškom plašila.”
And the AI says, "Poor Beatrice, a lonely spirit yearning for companionship. One day she stumbled upon an old abandoned mansion," etc.
A VI kaže: „Sirota Beatris, usamljeni duh koji žudi za drugarstvom. Jednog dana je nabasala na stari, napušteni zamak,” itd.
I encourage you all to hopefully one day try this. This is surprisingly fun.
Sve vas ohrabrujem da nadam se jednog dana isprobate ovo. Iznenađujuće je zabavno.
Now to even more directly hit this use case. And what I'm about to show you, everything I showed you so far is actually already part of Khanmigo, and what I’m about to show you, we haven't shown to anyone yet, this is a prototype. We hope to be able to launch it in the next few months, but this is to directly use AI, use generative AI, to not undermine English and language arts but to actually enhance it in ways that we couldn't have even conceived of even a year ago. This is reading comprehension. The students reading Steve Jobs's famous speech at Stanford. And then as they get to certain points, they can click on that little question. And the AI will then Socratically, almost like an oral exam, ask the student about things. And the AI can highlight parts of the passage. Why did the author use that word? What was their intent? Does it back up their argument? They can start to do stuff that once again, we never had the capability to give everyone a tutor, everyone a writing coach to actually dig in to reading at this level.
Sad da se još direktnije pozabavimo ovim načinom upotrebe. A ono što ću da vam pokažem, sve što sam vam do sad pokazao je zapravo već deo Kanmiga, a nešto što ću da vam pokažem nismo još nikome pokazali, radi se o prototipu. Nadamo se da ćemo ga objaviti u narednih nekoliko meseci, ali to je direktna upotreba VI, upotreba generativne VI, ne u podrivanju jezika i književnosti, već u hjihovom unapređenju na načine koji su nam bili nepojmljivi pre samo godinu dana. Radi se o razumevanju pročitanog. Đaci čitaju čuveni govor Stiva Džobsa na Stanfordu. I onda kako stižu do nekih tačaka, mogu da kliknu na to pitanjce. A VI će onda sokratovski, gotovo poput usmenog ispita, da ispituje đaka o pojmovima. VI može da istakne delove pasusa. Zašto je autor upotrebio tu reč? Šta mu je bila namera? Da li učvršćuje njegov argument? Mogu početi da rade stvari koje, ponovo, nikad nismo bili u mogućnosti da svima pružimo instruktora, učitelja pisanja da zapravo čitaju na ovom nivou.
And you could go on the other side of it. And we have whole work flows that helps them write, helps them be a writing coach, draw an outline. But once a student actually constructs a draft, and this is where they're constructing a draft, they can ask for feedback once again, as you would expect from a good writing coach. In this case, the student will say, let's say, "Does my evidence support my claim?" And then the AI, not only is able to give feedback, but it's able to highlight certain parts of the passage and says, "On this passage, this doesn't quite support your claim," but once again, Socratically says, "Can you tell us why?" So it's pulling the student, making them a better writer, giving them far more feedback than they've ever been able to actually get before. And we think this is going to dramatically accelerate writing, not hurt it.
A možete da se prebacite na drugu stranu. Imamo čitave procese koji im pomažu da pišu, pomažu da budu učitelji pisanja, da naprave skice. Međutim, čim đak zapravo sastavi nacrt, a ovde sastavljaju nacrt, mogu da traže sugestije, ponovo, kao što biste i očekivali od dobrog učitelja pisanja. U ovom slučaju, đak će reći, recimo: „Da li dokazi potkrepljuju moju tvrdnju?” A VI ne samo da je u stanju da da sugestije, već je u stanju da istakne određene delove pasusa i kaže: „U ovom pasusu, ovo baš i ne potkrepljuje tvoju tvrdnju,” ali opet, sokratovski kaže: „Možeš li da nam kažeš zašto?” Dakle, podstiče đaka, pretvara ga u boljeg pisca, dajući mu daleko više sugestija nego što je zapravo ikad pre bio u stanju da dobije. Smatramo da će ovo drastično da ubrza pisanje, a ne da ga osujeti.
Now, everything I've talked about so far is for the student. But we think this could be equally as powerful for the teacher to drive more personalized education and frankly save time and energy for themselves and for their students. So this is an American history exercise on Khan Academy. It's a question about the Spanish-American War. And at first it's in student mode. And if you say, “Tell me the answer,” it’s not going to tell the answer. It's going to go into tutoring mode. But that little toggle which teachers have access to, they can turn student mode off and then it goes into teacher mode. And what this does is it turns into -- You could view it as a teacher's guide on steroids. Not only can it explain the answer, it can explain how you might want to teach it. It can help prepare the teacher for that material. It can help them create lesson plans, as you could see doing right there. It'll eventually help them create progress reports and help them, eventually, grade. So once again, teachers spend about half their time with this type of activity, lesson planning. All of that energy can go back to them or go back to human interactions with their actual students.
Sve o čemu sam do sad govorio je za đake. Mislimo pak da bi ovo moglo da bude jednako moćno i za nastavnike da podstiče personalizovanije obrazovanje i iskreno da uštedi vreme i energiju njima i njihovim đacima. Ovo je vežba iz američke istorije na Akademiji Kan. Radi se o pitanju o špansko-američkom ratu. Prvo je u đačkom režimu. A ako kažete: „Kaži mi odgovor”, neće reći odgovor. Preći će u režim instruktora. Međutim, tom komandom koja je dostupna nastavnicima, mogu da isključe đački režim i da pređu u režim za nastavnike. A ono što postiže je da se pretvara u - Možete je posmatrati kao turbo vodič za nastavnike. Ne samo da može da objasni odgovor, već može da objasni kako biste to mogli podučavati. Može da pomogne nastavnicima da pripreme datu materiju. Može im pomoći da izrade planove rada, kao što možete videti ovde. Vremenom će im pomoći da naprave izveštaje o napretku i pomoći će im, vrememom, da ocenjuju. Opet, nastavnici provode oko polovinu vremena na ovom tipu aktivnosti, planiranje lekcija. Sva ta energija im se može vratiti ili se vratiti ljudskim interakcijama sa njihovim stvarnim đacima.
(Applause)
(Aplauz)
So, you know, one point I want to make. These large language models are so powerful, there's a temptation to say like, well, all these people are just going to slap them onto their websites, and it kind of turns the applications themselves into commodities. And what I've got to tell you is that’s one of the reasons why I didn’t sleep for two weeks when I first had access to GPT-4 back in August. But we quickly realized that to actually make it magical, I think what you saw with Khanmigo a little bit, it didn't interact with you the way that you see ChatGPT interacting. It was a little bit more magical, it was more Socratic, it was clearly much better at math than what most people are used to thinking. And the reason is, there was a lot of work behind the scenes to make that happen.
Znate, želim da istaknem jedno. Ovi veliki jezički modeli su toliko moćni da smo u iskušenju da kažemo, pa, svi ti ljudi će prosto da ih ubace na svoje veb-sajtove i nekako će pretvoriti same aplikacije u robu. A ja sam tu da vam kažem da je to jedan od razloga zbog kojeg nisam spavao dve sedmice kada sam u avgustu prvobitno dobio pristup GPT-4. Međutim, brzo smo shvatili kako bismo ga zapravo učinili magičnim, mislim da ste videli malčice sa Kanmigom da ne interaguje sa vama na način na koji ChatGPT interaguje. Malčice je magičnije, više je sokratovski, očito je mnogo bolji u matematici nego što većina ljudi smatra. A razlog je, mnogo rada je uloženo iza kulisa da se to ostvari.
And I could go through the whole list of everything we've been working on, many, many people for over six, seven months to make it feel magical. But perhaps the most intellectually interesting one is we realized, and this was an idea from an OpenAI researcher, that we could dramatically improve its ability in math and its ability in tutoring if we allow the AI to think before it speaks. So if you're tutoring someone and you immediately just start talking before you assess their math, you might not get it right. But if you construct thoughts for yourself, and what you see on the right there is an actual AI thought, something that it generates for itself but it does not share with the student. then its accuracy went up dramatically, and its ability to be a world-class tutor went up dramatically. And you can see it's talking to itself here. It says, "The student got a different answer than I did, but do not tell them they made a mistake. Instead, ask them to explain how they got to that step."
I mogao bih iščitati čitav spisak svega na čemu smo radili, mnogo, mnogo ljudi preko šest, sedam meseci kako bi delovao magično. Međutim, možda je intelektualno najzanimljivije što smo shvatili, a ovo je ideja istraživača iz OpenAI, da možemo drastično unaprediti matematičke sposobnosti i sposobnosti podučavanja, ako omogućimo VI da razmisli pre nego što progovori. Ako podučavate nekoga i momentalno počnete da govorite pre nego što pregledate njegov zadatak, možda nećete biti u pravu. Ako pak formulišete misli za sebe, a desno vidite da imamo stvarnu misao VI, nešto što pravi za sebe, ali ne deli sa đakom, time joj se tačnost drastično popravlja i njena sposobnost da postane vrhunski instruktor drastično skače. Ovde vidite kako priča sama sa sobom. Kaže: „Đak je dobio različit odgovor od mog, ali nemoj da mu kažeš da je pogrešio. Umesto toga, upitaj ga da objasni kako je došao do tog koraka.”
So I'll just finish off, hopefully, you know, what I’ve just shown you is just half of what we are working on, and we think this is just the very tip of the iceberg of where this can actually go. And I'm pretty convinced, which I wouldn't have been even a year ago, that we together have a chance of addressing the 2 sigma problem and turning it into a 2 sigma opportunity, dramatically accelerating education as we know it.
Dakle, prosto ću da završim, nadam se, znate, sve što sam vam upravo pokazao je samo polovina onoga na čemu radimo, i smatramo da se radi samo o vrhu ledenog brega onoga što bi ovo moglo da postigne. I prilično sam ubeđen, a ne bih bio pre svega godinu dana, da zajedno imamo priliku da se pozabavimo problemom dva sigma i da ga pretvorimo u priliku dva sigma, drastično ubrzavajući obrazovanje kakvo znamo.
Now, just to take a step back at a meta level, obviously we heard a lot today, the debates on either side. There's folks who take a more pessimistic view of AI, they say this is scary, there's all these dystopian scenarios, we maybe want to slow down, we want to pause. On the other side, there are the more optimistic folks that say, well, we've gone through inflection points before, we've gone through the Industrial Revolution. It was scary, but it all kind of worked out. And what I'd argue right now is I don't think this is like a flip of a coin or this is something where we'll just have to, like, wait and see which way it turns out. I think everyone here and beyond, we are active participants in this decision. I'm pretty convinced that the first line of reasoning is actually almost a self-fulfilling prophecy, that if we act with fear and if we say, "Hey, we've just got to stop doing this stuff," what's really going to happen is the rule followers might pause, might slow down, but the rule breakers, as Alexandr [Wang] mentioned, the totalitarian governments, the criminal organizations, they're only going to accelerate. And that leads to what I am pretty convinced is the dystopian state, which is the good actors have worse AIs than the bad actors.
Samo da zakoračim unazad, na meta-nivo, očito smo danas čuli mnogo debata sa obe strane. Neki ljudi zauzimaju pesimističniji stav prema VI, kažu da je zastrašujuća, imamo sve te distopijske scenarije, možda želimo da usporimo, želimo da pauziramo. S druge strane, imamo optimističnije ljude koji kažu, pa, i pre smo bili u prelomnim tačkama, prošli smo kroz industrijsku revoluciju. Bila je zastrašujuća, ali je sve nekako ispalo dobro. Nešto što bih sad tvrdio je da ne smatram da je ovo poput bacanja novčića ili da je ovo nešto gde ćemo prosto morati da sačekamo i vidimo kako će da ispadne. Smatram da smo svi ovde i napolju aktivni učesnici u ovoj odluci. Prilično sam ubeđen da je prva linija rezonovanja zapravo gotovo samoispunjavajuće proročanstvo, da ako bojažljivo delujemo i kažemo: „Hej, prosto moramo da prestanemo da radimo ove stvari”, zaista će se desiti da će poštovaoci pravila možda pauzirati, možda usporiti, ali kršitelji pravila, kao što je Aleksandr Vang pomenuo, totalitarne vlade, kriminalne organizacije, oni će samo da ubrzaju. A to vodi nečemu za šta sam prilično ubeđen da je distopijsko stanje, a to je da dobri akteri imaju goru VI od loših aktera.
But I'll also, you know, talk to the optimists a little bit. I don't think that means that, oh, yeah, then we should just relax and just hope for the best. That might not happen either. I think all of us together have to fight like hell to make sure that we put the guardrails, we put in -- when the problems arise -- reasonable regulations. But we fight like hell for the positive use cases. Because very close to my heart, and obviously there's many potential positive use cases, but perhaps the most powerful use case and perhaps the most poetic use case is if AI, artificial intelligence, can be used to enhance HI, human intelligence, human potential and human purpose.
Međutim, takođe, znate, obratiću se malo i optimistima. Ne smatram da to znači, oh, da, onda bi trebalo da se samo opustimo i nadamo najboljem. Ni to se verovatno neće desiti. Smatram da svi zajedno moramo vraški da se borimo da se postaramo da postavimo barijere, da postavimo - kad problemi iskrsnu - razumnu regulaciju. Međutim, da se vraški borimo za pozitivne vidove upotrebe. Jer blisko mom srcu, i očito ima mnogo potencijala za pozitivnu upotrebu, ali verovatno najmoćnija upotreba, a možda i najpoetičnija je ako bismo VI, veštačku inteligenciju, mogli da koristimo da unapredimo LJI, ljudsku inteligenciju, ljudski potencijal i ljudsku svrhu.
Thank you. (Applause)
Hvala vam. (Aplauz)