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EBay Spurns GameStop’s Bid as ‘Neither Credible Nor Attractive’ · Bloomberg Intelligence

0:02
Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. You're listening to the
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0:24
Speaker 2: One of the stories, Paul, that's Scott, you and me
0:26
Speaker 2: scratching our heads is eBay. Gamestop's bid for eBay, a
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Speaker 2: company that is four times its size. Ryan Cohen, of course,
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Speaker 2: making this very dramatic takeover offer for the company. eBay
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Speaker 2: has now rejected that fifty six billion dollar takeover offer,
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Speaker 2: calling it neither credible nor attractive. I think that pretty
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Speaker 2: much tells you what it thinks.
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Speaker 3: I did investment banking for a long time, and I
0:47
Speaker 3: can get it very creative with capital structures, but I
0:49
Speaker 3: have a hard time seeing how they're how they would
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Speaker 3: finance this thing.
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Speaker 2: All right, let's bring in Cecilia Denastasio. She is our
0:56
Speaker 2: video game reporter here at Bloomberg.
0:57
Speaker 4: Nice.
0:57
Speaker 5: Great to see you, Cecilia.
0:59
Speaker 6: Thank you for having me.
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Speaker 2: What was the thinking behind GameStop and making a bid
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Speaker 2: for eBay?
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Speaker 5: You know, we actually didn't get a.
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Speaker 6: Lot of insight into what CEO Ryan Cohen thought that
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Speaker 6: the proposed synergies could look like. He never really went
1:12
Speaker 6: out and said, hey, we run a video game, you know,
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Speaker 6: retail company, but also we're doing really well and collectibles.
1:18
Speaker 6: We're doing really well selling Pokemon cards. eBay also doing
1:22
Speaker 6: really well selling Pokemon cards and baseball cards. We could
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Speaker 6: have heard that in any of the interviews that Ryan
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Speaker 6: Cohen gave, but he didn't actually really go out and
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Speaker 6: say that. In fact, when he was given questions about
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Speaker 6: what the combined company could look like, you often sort
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Speaker 6: of dodged.
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Speaker 3: So, I mean, what's the story with GameStop these days?
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Speaker 3: I mean, I'm not a gamer, thank goodness, most of
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Speaker 3: my kids are not gamers. But it's almost a meme stock.
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Speaker 3: But what's the real call in this company these days?
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Speaker 6: You know, it's interesting because GameStop could be doing a
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Speaker 6: lot worse than it is doing. You know, they shuttered,
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Speaker 6: you know, thousands of stores over the last couple of
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Speaker 6: years to be a big ubiquitous presence at your neighborhood
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Speaker 6: strip mall. And you know, gamers are increasingly purchasing their
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Speaker 6: wares in online marketplaces and not at these at these
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Speaker 6: physical storefronts, but GameStop is still hanging on. CEO Ryan
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Speaker 6: Cohen said, you know, we could be doing worse. It's
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Speaker 6: not a great business, but it's hanging in there.
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Speaker 5: We could be doing worse.
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Speaker 2: It's not a great line that you want to hear
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Speaker 2: from the CEO of a company stock that you happen
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Speaker 2: to own. So having said all of this, there's been
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Speaker 2: some reporting that perhaps Ryan Cohen just wanted to boost
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Speaker 2: the stock price of game Stop because there's some clause
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Speaker 2: I guess in one of his compensation packages that if
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Speaker 2: the share price reaches a certain level, he gets another
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Speaker 2: big payout.
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Speaker 5: Can you talk us through what's.
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Speaker 6: Going on there, It's really hard to say. If the
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Speaker 6: companies did end up combining, then it's possible that he
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Speaker 6: would have been able to receive that payout and he
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Speaker 6: would have been very happy. But also at the same time,
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Speaker 6: a lot of analysts pointed out that the way that
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Speaker 6: Ryan Cohen approached eBay wasn't exactly so friendly. You know,
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Speaker 6: so he it was an unsolicited bid, he didn't publicly
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Speaker 6: state what he thought the synergies could look like. When
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Speaker 6: eBay came back saying that the deal felt neither credible
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Speaker 6: nor attractive. I think that kind of speaks to this
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Speaker 6: idea that you know, maybe this wasn't so thoroughly thought out.
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Speaker 6: I think a lot of analysts are very very confused
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Speaker 6: about the tent.
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Speaker 4: You did a lot to improve that outlook there. Yeah,
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Speaker 4: I mean that what a disaster that was.
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Speaker 3: So do you think game Stop would pursue a proxy
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Speaker 3: fight and take it to that next step?
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Speaker 5: It's possible.
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Speaker 6: You know, Ryan is a very unpredictable executive, which is
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Speaker 6: part of what makes him really fun to cover. He
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Speaker 6: has He posted a manifesto on x formally known as
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Speaker 6: Twitter describing how he thinks American business people are often
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Speaker 6: taking a really risk averse approach to running their companies
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Speaker 6: and he's really trying to carve out a model for
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Speaker 6: something really different. So it's possible he would pursue the
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Speaker 6: proxy fight. It's possible also that this was a publicity stunt.
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Speaker 3: Do we know whose advisors are his investment banking advisors?
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Speaker 3: The only thing I saw was he's got a financing
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Speaker 3: letter from TD Securities, which again tells you that highly confident,
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Speaker 3: highly confident for twenty billion dollars forty years.
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Speaker 4: But we don't really know who other advisors are.
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Speaker 6: He's a highly autonomous individual.
4:15
Speaker 5: Stay with us. More from Bloomberg Intelligence coming up after this.
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4:37
Speaker 3: Under Armour reported some numbers today. I didn't see them,
4:41
Speaker 3: but they can't be good. The stock's down sixteen percent here.
4:45
Speaker 3: But I know somebody who doesn't know what's going on here.
4:46
Speaker 3: Lillly Myers, she's a retail reporter for Bloomberg News, joining
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Speaker 3: us live here in our Bloomberg Interactive Broker studio. What
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Speaker 3: did under Armour have to say that maybe the market
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Speaker 3: didn't go for.
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Speaker 7: Yeah, so I think under Armour disappointed investors. I think
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Speaker 7: that they're the revenue for next year or this current
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Speaker 7: year is not not as high as they expected, and
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Speaker 7: their earnings per share was also lower.
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Speaker 5: They also mentioned the Middle East conflict.
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Speaker 7: As impacting their sales and the split from the Steph
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Speaker 7: Curry brand hitting their bottom line.
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Speaker 4: My question with under Armour, I'm a Nike person, by
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Speaker 4: the way.
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Speaker 3: Full disclosure always happened, and I'm not switching, but it's competitive.
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Speaker 3: I mean, there's Nike out there body dust for those
5:28
Speaker 3: of us in the know, we pronounce it that way, and.
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Speaker 4: I'm just not sure. And it's there's so many niche players.
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Speaker 3: I mean, the kids here at Bloomberg they were in
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Speaker 3: all different kinds of sinkers that I've never seen before.
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Speaker 4: How does under Armour fit in there, do you think?
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Speaker 8: Yeah?
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Speaker 7: I mean I think it's a really competitive space, like
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Speaker 7: you described, both on.
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Speaker 5: The footwear side and the apparel side.
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Speaker 7: You know, under Armour is part of this restructuring plan
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Speaker 7: that they've been going through recently, has been trying to
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Speaker 7: really slim down the number of skews that they sell,
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Speaker 7: you know, kind of streamline the products and also cut
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Speaker 7: back on their discounts.
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Speaker 3: So is this you know, I understand that it's really
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Speaker 3: a product driven business. You can't just crank out the
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Speaker 3: same sneaker year after year after year. I mean every
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Speaker 3: year it's like fat it is fashion. Do they have
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Speaker 3: the resources, they have the capabilities to really compete against
6:16
Speaker 3: the I guess the bigger players.
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Speaker 7: Yeah, I mean it'll be interesting to see. The hard
6:20
Speaker 7: thing with some of the retail innovation cycle is that
6:23
Speaker 7: it takes like eighteen months, you know to start seeing
6:26
Speaker 7: some of that new product actually hit the shelves. So
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Speaker 7: I'll be interested to see what they come out with.
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Speaker 3: You mentioned they.
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Speaker 4: Lost Steph Curry. That's a big name.
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Speaker 3: How do they think about using athletes as part of
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Speaker 3: their marketing promotion?
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Speaker 4: Strategy is a core to them? And how big of
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Speaker 4: a loss was like Steph Curry?
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Speaker 7: Yeah, so for Steph Curry, I mean that was a big,
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Speaker 7: a big deal. They had worked with the Curry brand
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Speaker 7: for a long time. That was a really essential part
6:56
Speaker 7: of their basketball business. So this quarter they said that
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Speaker 7: for this coming year, the Curry brand separation made it
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Speaker 7: so that their revenue was down slightly. If they had
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Speaker 7: stayed with Curry, it would have been flat for the year.
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Speaker 5: So it'll be interesting to see, you know, if they.
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Speaker 7: Try and side more big names or what comes next.
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Speaker 3: I mean, there's kids coming out of college every year.
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Speaker 3: Are they going to be aggressive?
7:19
Speaker 4: What did they say? Their strategy is there because it's.
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Speaker 3: A tried and true strategy, particularly for athletic where Nike's
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Speaker 3: seen it. I mean, Michael Jordan, you know, that's the
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Speaker 3: great example. But are they committed to that part that strategy,
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Speaker 3: do you think.
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Speaker 5: Yeah, that's a good question. I mean, they definitely work
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Speaker 5: with athletes.
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Speaker 7: I'm curious to see how that will evolve moving forward,
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Speaker 7: especially without Curry.
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Speaker 3: What's the uh, what's the tariff situation with some of
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Speaker 3: these shoot companies these days?
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Speaker 4: I mean is it? Do they even talk about it anymore?
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Speaker 3: Because I know a lot of the retail companies they
7:52
Speaker 3: used to others as well, used to just give you
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Speaker 3: a number. It costs US five hundred million this quarter
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Speaker 3: or forty million this this quarter. Is still an issue
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Speaker 3: for these apparel companies.
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Speaker 5: Yeah, it's interesting. So it's switched a little.
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Speaker 7: Now they're talking about what their expected tariff refund will be,
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Speaker 7: so they're.
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Speaker 5: Baking that in or on the positive side.
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Speaker 7: I think, you know, there's a lot we still don't
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Speaker 7: know about what companies will get out of tariff refund,
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Speaker 7: if they'll get the full amount, what that process will
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Speaker 7: actually look like, how long it will take. But that's
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Speaker 7: the discussion now, is you know the upside from that refund?
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Speaker 3: Now companies have actually you have to go like file
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Speaker 3: and say I want a refund right now?
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Speaker 4: Has the Nike done.
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Speaker 3: It something like I'm thinking of the big big name
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Speaker 3: in your retail.
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Speaker 4: Has Nike actually done that for example?
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Speaker 7: Yeah, so a lot of major retailers have have sued
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Speaker 7: for tariff refunds, and I think it'll be interesting to
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Speaker 7: see as as they become more of a reality, how
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Speaker 7: companies will go about it.
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Speaker 3: There still really isn't a stre There isn't I guess,
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Speaker 3: a policy framework to get the money right.
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Speaker 4: They're still working on that.
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Speaker 7: From my understanding, I think it's it's it's still in process.
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Speaker 4: How much is if Nike gets money they do with it?
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Speaker 4: Do they give it back to me? Who paid a
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Speaker 4: tariff on my kicks?
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Speaker 9: Here?
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Speaker 4: We don't know that.
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Speaker 7: Yeah, I mean, I think that will be really an
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Speaker 7: interesting thing to watch. I think consumer reaction will be interesting,
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Speaker 7: you know, consumers who have had to face those higher prices,
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Speaker 7: but also the company that's haed to shoulder a lot
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Speaker 7: of it.
9:18
Speaker 10: Stay with us.
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Speaker 4: More from Bloomberg Intelligence coming up after this.
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9:39
Speaker 3: All right, So President Trump leaving today for Chinese has
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Speaker 3: got a plane full of executives.
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Speaker 4: Including executive for Boeing, Yep and Boyden.
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Speaker 3: You think about a company that's leveraged to Chin it
9:50
Speaker 3: a I always think of Apple, But Boeing's right there.
9:53
Speaker 3: And we want to talk to Sid Philip about that,
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Speaker 3: Bloomberg Chief correspondent for Global Aviation, because this could be
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Speaker 3: one of those trips where somebody, you know, China announces
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Speaker 3: a gazillion plane deal and you.
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Speaker 2: Know, actually something that the CEO has kind of hinted
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Speaker 2: at already saying that you know, Trump's visit would be
10:13
Speaker 2: quote a meaningful opportunity for us.
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Speaker 3: Yeah, Sid Philip, he does all this stuff for Blomberg News.
10:18
Speaker 3: What are you expecting here on this trip for Boweing?
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Speaker 3: What do you think Boeing wants to get out of this?
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Speaker 8: So Boeing's looking to secure its first big order from
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Speaker 8: China in almost a decade, and so we understand it's
10:29
Speaker 8: going to be five hundred seven three seven Maxes and
10:33
Speaker 8: a large number of white body planes, and that would
10:36
Speaker 8: be significant because the Chinese airlines haven't really ordered any
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Speaker 8: Boeing planes in a while and.
10:43
Speaker 4: Just because they're mad at us.
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Speaker 8: They were mad at and there was COVID in the
10:47
Speaker 8: middle of it. And so the Chinese airlines actually need
10:50
Speaker 8: those planes because they don't really have a supply of Boeing.
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Speaker 8: I mean, they operate both Airbus and Boeing planes, and
10:56
Speaker 8: they don't really have a supply of planes beyond the
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Speaker 8: twenty thirties. And so if they want to keep expanding,
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Speaker 8: if they want to keep adding more service, they need
11:04
Speaker 8: those planes, and disorder is a way to get that.
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Speaker 5: Okay, so this order is a way to get that.
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Speaker 5: I guess if you're.
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Speaker 2: An airliner, you're thinking, what's the next thing Boeing is
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Speaker 2: selling that I want to get my hands on. I mean,
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Speaker 2: you know, not tomorrow, not next month, but down the
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Speaker 2: road as I plan my fleet.
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Speaker 5: Does boe have an answer to that?
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Speaker 2: Because it feels like the company has spent so much
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Speaker 2: time writing itself that it hasn't really put as much,
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Speaker 2: at least outward energy into innovating the next jet.
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Speaker 8: So that's that's the really big question that the CEO,
11:35
Speaker 8: Kelly Ottberg's really looking at. So while obviously you have
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Speaker 8: the short term and the immediate issues that they have
11:42
Speaker 8: to ramp up production, they have to ramp up cash
11:44
Speaker 8: like cash generation reduce that debt pile.
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Speaker 10: The bigger question for Boeing is where do they go
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Speaker 10: from here?
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Speaker 8: And the seventry seven is basically a long derivative of
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Speaker 8: a nineteen sixties jet, and so for Boeing they need
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Speaker 8: to decide what the do next, and that will be
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Speaker 8: crucial in the sort of deeoperly that they have with Airbus,
12:04
Speaker 8: and Airbus has been talking about how they are working
12:07
Speaker 8: on their next generation of product that they're aiming to
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Speaker 8: get out in the middle of next decade, and that
12:13
Speaker 8: would basically allow airlines to get something that's more fuel
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Speaker 8: efficient and allows them to fly greater distances with more
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Speaker 8: passengers on them. And so what we understand is that
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Speaker 8: Boeing is working on something that's more evolutionary rather than revolutionary,
12:29
Speaker 8: because the last thing airlines need is uncertainty. And when
12:33
Speaker 8: you have a product that's revolutionary, it always comes with
12:37
Speaker 8: deathing issues. It comes with all sorts of complications with
12:40
Speaker 8: new technology and how that whole measures together with existing infrastructure.
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Speaker 5: Yeah, we've seen that play UPFT exactly.
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Speaker 8: And so for the airlines, they want something that stable
12:49
Speaker 8: allows them to sort of keep going as usual and
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Speaker 8: not sort of rocking the boat too much.
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Speaker 10: And that's really key for Boeing.
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Speaker 8: So how do you derive more fuel efficiency using evolutionary technology?
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Speaker 8: And that's where we see Boeing sort of going in
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Speaker 8: terms of their next products.
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Speaker 3: Ten seconds, if I get a big order today from China,
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Speaker 3: they can't even make the planes bowing.
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Speaker 4: I mean they have to build another factory or two.
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Speaker 8: So Boeing is in the process of opening a new
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Speaker 8: factory for the seven three seven, and they are looking
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Speaker 8: at ramping up production and they've been talking about how
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Speaker 8: they've got these short term goals. So they're currently looking
13:26
Speaker 8: at forty two a month. They're going to ramp up
13:28
Speaker 8: to forty seven a month, then fifty two a month
13:30
Speaker 8: and sixty So essentially for Boeing that they have a
13:34
Speaker 8: sort of stepped up plan to ramp up production depending
13:37
Speaker 8: on how the FA sort of signs.
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Speaker 5: Off on it, and product will be in the US.
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Speaker 10: They will be in the US, so Boying produces all
13:42
Speaker 10: its planes in the US. Stay with us.
13:45
Speaker 4: More from Bloomberg Intelligence coming up after this.
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14:01
Speaker 1: wherever you get your podcasts, or watch us live on
14:05
Speaker 1: YouTube AI.
14:06
Speaker 3: It's impacting seemingly all parts of our life, all parts
14:10
Speaker 3: of business and the economy, and that includes weather forecasting.
14:14
Speaker 3: But maybe some shortcomings there. Our next guest has some
14:17
Speaker 3: thoughts there at Caatham Kunda. He's a lecturer at the
14:19
Speaker 3: Yale School of Management and he is a Bloomberg Opinion contributor.
14:23
Speaker 3: You say AI isn't built for bad weather's Black Swan era?
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Speaker 4: What do you mean by that? Gotham?
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Speaker 10: Hey, Paul, good to be back.
14:30
Speaker 9: So it's about weather forecasting, but it's not just about
14:33
Speaker 9: weather forecasting. It's about the fact that we're using AI
14:37
Speaker 9: all over the place as a tool to use the
14:40
Speaker 9: past to predict the future, which is maybe the most
14:43
Speaker 9: fundamental of all human activities, and it's incredibly important. And
14:47
Speaker 9: it turns out that if as long as you have
14:49
Speaker 9: enough and rich enough data about the past, AI can
14:53
Speaker 9: be incredibly good at it, even better than the tools
14:55
Speaker 9: we've used in the past, which in the case of
14:57
Speaker 9: weather forecasting, involve planes and physics models and supercomputers and
15:02
Speaker 9: weather satellites. So all of that is great. The problem
15:06
Speaker 9: is that the weather is changing, so the weather of
15:10
Speaker 9: the past may not be a good guide to the
15:12
Speaker 9: weather of the future. And AI is incredibly good at
15:16
Speaker 9: understanding stuff that happened within its training data set, and
15:19
Speaker 9: incredibly bad about understanding stuff that's happening outside its training
15:23
Speaker 9: data set. And as I said, that is about weather forecasting,
15:26
Speaker 9: but it's not just about weather forecasting. It's about anywhere
15:29
Speaker 9: where we're facing this problem of using the past to
15:31
Speaker 9: predict the future. But the past is not like the future.
15:35
Speaker 2: And in your column you write it will work right
15:38
Speaker 2: up until it doesn't. AI models have a tendency to
15:40
Speaker 2: fail in the biggest moments. And one example you give
15:44
Speaker 2: that I think anyone who's over the age of eighteen
15:47
Speaker 2: can relate to is the value risk models that banks
15:50
Speaker 2: use during the Great Financial Crisis, where they relied on
15:54
Speaker 2: past data to predict how much risk they can each
15:57
Speaker 2: take on.
15:58
Speaker 9: That's right, And that's another case of a tool that
16:00
Speaker 9: works really, really well under normal circumstances, so well that
16:04
Speaker 9: it gives you confidence, right, it makes you start to
16:06
Speaker 9: rely on the tool. You might even enshrine it in
16:09
Speaker 9: regulations so that when it fails, it's not just a
16:12
Speaker 9: normal failure, it's a catastrophic failure.
16:14
Speaker 10: So that's one layer of problem.
16:16
Speaker 9: The second layer is that often these tools, it can
16:18
Speaker 9: start to get used by people who aren't they people
16:20
Speaker 9: who built them, and so who don't necessarily understand them
16:22
Speaker 9: very well. I was at MIT during the to the
16:25
Speaker 9: financial crisis, and I remember a very senior risk management
16:28
Speaker 9: person at one of the banks at MIT saying to
16:31
Speaker 9: a group of us, you know, I saw six sigma
16:34
Speaker 9: events on three consecutive days, so the markets are weird.
16:38
Speaker 9: And I just stared at him and I said, that
16:40
Speaker 9: doesn't mean that the markets are weird. It means that
16:43
Speaker 9: your tool has failed, because six sigma events three days
16:47
Speaker 9: in a row will not happen in the entire lifespan
16:51
Speaker 9: of the universe. Right, That's how rare we're.
16:54
Speaker 10: Talking about is.
16:55
Speaker 9: And this was a person who, you know, they were
16:57
Speaker 9: very smart, but they didn't understand what this meant.
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Speaker 3: So, you know, I think one of the AI question
17:04
Speaker 3: marks Gotham right now, is is AI going to create
17:08
Speaker 3: jobs in this economy or destroy jobs in this economy?
17:11
Speaker 3: I'm not sure we know that, do you have any
17:13
Speaker 3: thoughts on that.
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Speaker 9: Well, I think we know that the answer is both,
17:17
Speaker 9: it's going to create it's going to destroy some jobs,
17:20
Speaker 9: it's going to create others. But the data on AI
17:23
Speaker 9: job described destruction, the actual empirical data is pretty weak.
17:27
Speaker 10: It looks more.
17:28
Speaker 9: Like companies that over hired or that are looking to
17:30
Speaker 9: cut costs and are kind of blaming AI for what
17:33
Speaker 9: they did. But at the same time, there are going
17:37
Speaker 9: to be some big transitions, and you know, all of
17:39
Speaker 9: the standard models that we have, they're all about like
17:42
Speaker 9: you know, bank tellers or things like that that tell
17:44
Speaker 9: us new technologies don't create jobs, don't don't destroy jobs,
17:48
Speaker 9: they don't destroy jobs and aggregate, but they destroy some jobs,
17:50
Speaker 9: and the transition can be really hard for the people
17:53
Speaker 9: who are undergoing through it.
17:55
Speaker 2: So you are lecturer at the Yale School of Management,
17:58
Speaker 2: How does education prepare young people? Graduates, those who have
18:04
Speaker 2: some working experience, are going back to school and want
18:07
Speaker 2: to come out, you know, with a better skill set
18:09
Speaker 2: to prepare for this world.
18:10
Speaker 9: So I think there are two things we need to
18:12
Speaker 9: think about really hard here. One is that one of
18:14
Speaker 9: the really interesting things about AI, at least as it's
18:17
Speaker 9: currently structured, is it seems to be a magnifier, not
18:20
Speaker 9: a compressor. Right, So if you think about like power tools,
18:24
Speaker 9: power tools and construction equipment made brute physical strength less
18:28
Speaker 9: important if you were working in manual labor. So they
18:31
Speaker 9: compressed the differential and productivity between people who were physically
18:35
Speaker 9: very strong and people who were less strong. But there
18:38
Speaker 9: are other sorts of technologies that they increase the differences
18:41
Speaker 9: in capability, so someone who normally would be twice as
18:43
Speaker 9: capable becomes ten times as capable. AI looks more like
18:47
Speaker 9: something in the second pool, right. It looks like it
18:50
Speaker 9: takes people who are good and it makes them great,
18:52
Speaker 9: but it's not that useful if you're not already an
18:54
Speaker 9: expert in the field, and so someone has to create
18:58
Speaker 9: those experts. That's the second That's what the one thing
19:00
Speaker 9: that schools can do. The second thing is that schools
19:03
Speaker 9: are you know, like at their best, and not all
19:05
Speaker 9: schools do this all the time. I'm not defending that
19:08
Speaker 9: saying that at all, but at their best, schools can
19:10
Speaker 9: learn teach people to think independently of these skill sets.
19:14
Speaker 9: And you're even seeing AI companies coming out and saying
19:16
Speaker 9: that like humanity skills are really really important, that's what.
19:21
Speaker 10: Yeah.
19:21
Speaker 9: So, so something I've been I've been quoting at all
19:23
Speaker 9: my programmer friends with great joy is when there was
19:26
Speaker 9: all this turmoil before, people were saying they would you
19:29
Speaker 9: know the responsibilities, but you guys need to learn to code, right,
19:31
Speaker 9: And so now the AI is doing the coding, and
19:33
Speaker 9: I said, you guys need to learn to ode.
19:38
Speaker 3: I mean that kind of goes to one of the
19:40
Speaker 3: things I'm learning from the young folks is it's the
19:44
Speaker 3: ability to ask AI the right question, the prompts, yes,
19:48
Speaker 3: the prompts, and in your world and your day to
19:51
Speaker 3: day at a university environment, gotam, How's AI impacting your world?
19:56
Speaker 9: So a lot in multiple different ways. So it's but
19:59
Speaker 9: I'll it's not just learn the prompts, it's you have
20:02
Speaker 9: to know enough to know when the AI is wrong.
20:06
Speaker 9: That is actually I found the single most important skill.
20:08
Speaker 9: So I used AI to help me create the syllabus
20:11
Speaker 9: for a course.
20:12
Speaker 10: It was amazing.
20:13
Speaker 9: It took what would have been a week of work
20:15
Speaker 9: and let me do it in a day. I was
20:17
Speaker 9: blown away. But several of the things that it gave
20:20
Speaker 9: me were wrong in ways that you had to be
20:22
Speaker 9: an expert to understand. We're wrong, but another expert we've
20:26
Speaker 9: seen this and thought I was need it right. So
20:30
Speaker 9: that was a really important distinction. And what you're seeing
20:34
Speaker 9: first is, you know, look, cheating is a huge problem.
20:36
Speaker 9: Like we've had to crack down on that, like written exams,
20:41
Speaker 9: take home exams. I think, like, I'm really sorry to
20:44
Speaker 9: hear that, see that happening, But it's really happening. And
20:47
Speaker 9: I tell my students on the first day, I'm like,
20:50
Speaker 9: you probably can cheat. And you know, look, honestly, I
20:53
Speaker 9: can't tell you if I'm going to catch you or not, right,
20:55
Speaker 9: Like the tools to catch you are not that great,
20:57
Speaker 9: but you're gonna cheat yourself. Like what you want here
21:01
Speaker 9: isn't the grade. Nobody cares about your grades. What you
21:04
Speaker 9: want is the learning, and you get the learning from
21:06
Speaker 9: doing the work, not by asking trat ept to do
21:09
Speaker 9: it for you.
21:12
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