#imo olympiad

[cfalindia]

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[supriyawithoutsu]

🥲

[straightlightyagami]

part of me regrets not trying to apply to universities in the US (even though realistically it’s too far away and too complicated a process and too expensive) bc I wonder if I could have gotten into the US top 10 ones or whatever

[townpostin]

India's Unprecedented Success in Maths Olympiad: An Unsung Story

India’s exceptional achievement in the International Math Olympiad 2024, with four gold and one silver medal, receives little recognition in a country obsessed with cricket and films. India’s brilliant performance in the International Math Olympiad 2024, winning four golds and one silver, remains overshadowed by the nation’s focus on cricket and films. Indians who love cricket and films to the…

[rahulrainbow]

WHICH OLYMPIAD IS BEST OR AUTHENTIC AT SCHOOL LEVELS?

Which Olympiad Is Best Or Authentic At School Levels? Recently, the 64th International Mathematical Olympiad (IMO) 2023 held at Chiba, Japan (July 2-13, 2023). Here, the six-member Indian team secured 2 Gold, 2 Silver and 2 Bronze medals. . India’s rank is 9th out of 112 countries. Homi Bhabha Centre for Science Education, Mumbai (HBCSE) is core organisation for participation in International…

[ickysubbyboi]

hey pretty, please talk more about more stuff that you like, you’re so cute <3

Another one that I haven’t really talked about is liking math but not in a normal way probably more like a degenerate way…

Growing up I was like a lot into it. I used to compete in those math Olympiad tournaments. And as any other regular normal kid my dream was to go to the IMO (like the highest level international Olympiad) which is unrealistic af but I only found out that years later…

When I was in high school I started going to these other courses math course offered by my local university, which was 100% focused on math competitions. And you took like Number theory, algebra, geometry and combinatorics (number theory is obviously the nicer one) and they were really hard, some of it was in a college level so that’s probably why. But it’s funny how I was pretty average on those and it wasn’t easy for me. But on my class there was this dude who’d sit at the back and read books because the already college level math was too boring for him (he was like 14 💀) so it puts into perspective how good some of these people are…

Another weird thing is that at school sometimes I’d do math in even non math related classes 😭 and I never liked notebooks so I’d write stuff down on my table then erase it afterwards…pretty sure I got in trouble at some point for that but it was so much easier

One time when I was like 13/14 me and a couple friends decided to calculate 38! Factorial by hand (terrible idea) to calculate the total amount of possibilities we could arrange all students on the class room. This took hours, I mean hours we pretty much spent the whole school period doing it, for some reason I still don’t know why. There are more math related stories I think but I already typed way too much so…anyways. I almost ended up doing a mathematics bachelors but I went for engineering instead. But I’ll probably do a double major, or at least a mathematics minor just for fun

38! Is equal to: 523022617466601111760007224100074291200000000

Just to put into perspective how stupid that is 😭

[gamingavickreyauction]

I haven't seen anyone talk yet about the fact that an AI solved 4/6 of this year's IMO problems. Is there some way they fudged it so that it's not as big a deal as it seems? (I do not count more time as fudging- you could address that by adding more compute. I also do not count giving the question already formalised as fudging, as AIs can already do that).

I ask because I really want this not to be a big deal, because the alternative is scary. I thought this would be one of the last milestones for AI surpassing human intelligence, and it seems like the same reasoning skills required for this problem would be able to solve a vast array of other important problems. And potentially it's a hop and a skip away from outperforming humans in research mathematics.

I did not think we were anywhere near this point, and I was already pretty worried about the societal upheaval that neural networks will cause.

[mt-lowercase-m-derogatory]

So I have my second adhd evaluation in a week and like

I've been trained for years to on how to sit down for 4.5 hours while working on 3 particularly obtuse math problems. Mathematics Olympiad shit. I've won medals on an international level [not technically IMO tho so I'm not valid, I know this].

And maybe that should be taken into account when a "slightly above average" result on the computerised test is found during my adhd eval. Which is carried by me being in the top 1% for response speed because that part goes by quicker if you answer the questions faster.

[myjunkisyuzuruhanyu]

I see people talk about Shoma being over scored. I dont know how scoring works exactly. I know a double jump / combination jump? / is obligatory in the short program. Because Shoma fell and didnt do the two jumps I thought he would be below 3 place. Then he was not.

Was he over scored?

There was someone comparing Shoma now with Hanyu at the Olympiad. That Hanyu was under scored then and Shoma over scored now. Was Hanyu under scored?

Please keep in mind that I am no judging expert and that I solely give my opinion on the scoring. You can always discuss my point of view and I will always explain my opinion to my abilities. I may not be an expert but if I express my opinion I do it on arguments and explanations. And you can always demand explanations for statements like "xy skater was overscored" if they can't explain it their argument is invalid. And also always keep in mind that fans have favorites and skaters they dislike, no one is really objective, not even the judges.

There are different questions in this mixed up together as I understand it, let me unravel it a bit. The reply will be rather long and I hope you can even understand what I am trying to say. I hope you understand the basics like BV (base value) and GOEs (grades of execution) and PCS (program component score) because I can't start from scratch with my answer.

A) One is your own perspective and question how scoring works that you didn't understand why Shoma was still 2nd place? Was he overscored to get there?

B) The perspective and opinion you read from others that Shoma is/was overscored and if that's true? And where do they come from

C) Shoma SP now vs. Yuzu SP at Olympics?

D) Was Yuzu underscored at the Olympics? Underscored in general?

A) Why was Shoma still 2nd place?

You are right that skaters have to perform one jump a triple or quad in combination in the SP, it's a requirement. If you don't complete a combination, the GOEs on this element is minus 5. Means that no matter if you land the first jump of the combination or not you will have - 5 GOEs deductions. (a minus GOEs of 5 is not 5 in the end, there is a percentage to the Base Value that gets deducted)

Let's get back to Shoma, Shoma did have no combination and fell. A fall will also give you minus 5 GOEs on the jumping pass. So because Shoma fell it didn't matter if he got the +Combo deduction or not (contrary to Skate Canada where he still landed the 4T but had no combination) He won't be penalized two times for the same mistake.

Even with the fall Shoma had the 3rd highest BV of the competition of 42,5. Even with a fall it was only 2 points lower than Sota Yamamoto's (BV 44,0) and Adam Siao Him Fa's (BV 44,8). This alone speaks volumes of his technical ability that even with a jump missing he still had a comparable BV.

Despite the fall the rest of Shoma's elements was amazing. He had a good landing on his other two jumping passes the 4F and the 3A and got good GOEs on both. His spins are the best of the field and two of them easily earned him Level 4 and high GOEs and one had Level 3. His step sequence was also the best of the field with clear deep edges, superior upper body work, difficult steps and turns executed in the music. Shoma won 1,56 GOE alone on the steps. (Only Junhwan Cha and Shoma had Level 4 on their step sequence) Shoma won the PCS category with 44,37 which is rightfully higher than those of the rest because he has the best skating skills, superior ice coverage, he has much more speed than everyone else there and on top he can interpretate and perform his music and despite the mistake never gave up on any of it.

In conclusion the quality of his other elements made up for the fall to still get him 2nd place.

Was Shoma overscored? Imo not at all. He got the minus points he should get, all judges gave the fall minus 5 GOEs and he got the required point deduction for the fall at the end. His PCS were normal or even low for his standard, because for a clean performance he scored 46-47 last season and throughout the years he scored 44 PCS quite regularly for programs with mistakes. (but tbf we can't compare PCS scores like that because the categories have been reduced from 5 to 3). For a clean SP with a combination of 4T3T Shoma scored 105+ up to 109 points. So deduct only the 4T3T (13,7 BV for 4T3T, Shoma still got 4,75 for his 4T+Combo = 13,7 - 4,75 = 8,95) So if Shoma can score 105+ for a clean SP and you deduct the 8,95 you would have at best a score of 96 points minus 1 for the fall, so roughly 95 points. Shoma got 91,66, so nothing extraordinarily high compared to what he usually gets among judges.

Now you will have ppl telling you that those 105+ scores were overscored as well etc, but even if you deduct from let's say 100, it's still not below 90 points. And anyone who says Shoma doesn't deserve any points at all for his jumps you cannot take seriously anyway.

This brings us to point B)

B) Was/Is Shoma overscored? opinions and where they come from:

There are ppl in this fandom that ever since Shoma turned senior (and some even before that) claimed that Shoma is overscored.

One criticism that I can understand is Shoma's jumping technique. Shoma's jumping technique is far from ideal as he doesn't have a clear toepick - some would call it blade assistance but that is debatable among experts and fans alike. He has issues with prerotation and critics call it excessive prerotation. There is however discussion about at what point prerotation should be deducted and there is also a rule problem as judges are not allowed to use slow motion on the take-off to look for prerotation which imo leads it to it basically never being applied negatively to anyone at all. Let's be real lots of skaters prerotate excessively (a certain degree of prerotation is normal though for most jumps due to body pyhsics) and imo if everyone is getting a pass on it, it would be rather weird to just penalize Shoma for it. And imo yes Shoma prerotates his jumps far more than for example Yuzuru Hanyu, but I think compared to the past, it's gotten a lot better. If there should be a penalization at all for it, it should be seen on GOEs if you consider prerotation as bad take-off. (I don't see it being applied by judges though) So while I understand this part of the criticism it's not like all of Shoma's jumps are problematic. His Axel jump is just fine, his edge jumps like Salchow and Loop, jumps proned for more prerotation due to physics, are not worse at take-off than that of most skaters, it's normal. I can understand that the 4F getting such high GOEs is a point to criticize however his 3A deserves high GOEs and other points aside from the take-off matter too and Shoma excells in them in comparison to other skaters. (I won't explain all the criterias as this would lead to far)

Another point that I see as valid criticism is that Shoma doesn't use as much onefoot skating and is often on two feet. This is mostly true, but it doesn't mean that his linking elements and transitions aren't there. Some call his programs empty, but please compare his linking elements to those you have seen today for example. He does have a much more complex program than some give him credit for. Just because there is one thing (one foot skating) that he can improve doesn't mean the rest isn't difficult or not worth the scores he receives.

There is criticism in everything else Shoma does as well, but tbh I don't think other criticisms are valid at all. Shoma is one of the best spinners and has tremendous steps, he is one with the deepest edges and fast speed, he covers the whole ice and he has a musicality and connection to music like no other, so imo his PCS being high is deserved imo they were even often too low. Same for spins and steps. And if you compare his jumps to other skaters in lower rankings you can see why he gets good GOEs on them.

I think while some criticism is valid and can be seen as "Shoma is overscored" there are enough examples where Shoma didn't earn the points he should get for elements or PCS. So even if his 4F is sometimes overscored, his spins are often underscored and PCS too and imo for me it evens it out. I don't deny that at some competitions Shoma was judged quite favorably, but there are other examples (CoR 2019, Skate Canada 2022...) where it was quite the opposite. Tbf I think Shoma is one of the skaters that is quite in favor with judges but this is mostly because of what qualities he has and what capabilities he has that even on a bad day some things are judged less harshly but I think that top skaters do get a pass for some things isn't as unusual and definitely not a Shoma overscoring problem but a reputation judging problem in general.

I could name a few other reasons why fans keep on insisting on the tale that Shoma is overscored and favored but it would lead to far into fandom drama. Let me just tell you that a huge share of ppl who criticize Shoma don't like him at all and some would probably even complain if he would get 0 points and still call it too high.

Also tbh I think in my time in the fandom - more than 10 years now - I always saw fans complain about top skaters being overscored depending on who they liked better. I saw it about Shoma, but also about Yuzu and almost everyone who ever won medals in figure skating since the new scoring system. What matters in the scoring in the end is that the right ppl take the medals home and imo there are cases where I think results could be reversed, but I can see arguments for both sides. I always try to see the whole picture and every perspective, but as a Shoma fan I am certainly biased for Shoma too. No one here is objective. So my opinion is also just one in a few.

Imo Shoma isn't more or more often overscored than anyone else of his high caliber. He isn't liked among skating experts, judges and fans for nothing.

C) Shoma SP now vs. Yuzu SP at the Olympics?

I don't know how you can compare those two short programs because first it's a whole different judging panel, 2nd the rules have changed for PCS ( Program Component Score - 3 categories instead of 5) and even if you leave the other two reasons I mentioned before behind the mistakes from Shoma and Yuzu were different. Yuzu at the SP at the Olympics missed a complete jumping pass - scoring 0 points for his element that was supposed to be a 4S. Shoma at NHK did jump his 4T even if it resulted in a fall - so Shoma still got 4,75 points for it. Let's still compare it because it has been done: Yuzu got 95,76 for his SP at the Olympics with a 0 points jumping pass. Shoma at NHK got 91,66 with a jumping pass that still had 4,75 points to it. The PCS of Shoma were 44,37, Yuzu's were 47,08 (which is higher than a PCS score with a PCS cap due to major error in the rulebook should happen). Btw at the GPF 2019 Yuzu scored 97, 43 with a similar mistake (no combo, just that he didn't fall) that Shoma did in his SP at NHK. You can see that Yuzu's scores for similar mistakes were even higher than what Shoma got. Now we can argue about if Yuzu has more quality on his elements than Shoma overall (imo on jumps definitely) so that Yuzu's scores with those mistakes are still fair or even as other opinions suggest too low. As I said before it will matter who you ask.

I think comparing scores from different competitions is always a bit tricky. Because even if in general scores should be comparable overall, it's common knowledge that it's just not true. It always depends on who are the judges and how strict are they.

On top such comparisons between Yuzu and Shoma always make me quite unhappy, because why is Shoma's scoring always compared to Yuzu's? Yuzu didn't compete at NHK. I would totally get a comparison to Sota Yamamoto who won the SP at NHK, but Yuzu? Just why? If there is talk about Shoma's scoring, it's always Yuzu who is brought up by a certain amount of fans mostly rabid Fanyus. Also Yuzu is not competing anymore, it's pointless to still look at Yuzu's scores as they have 0 influence in the current scoring, nor on Yuzu's personal life or any kind of politicking in skating.

D) Was Yuzu underscored at the Olympics? Underscored in general?

I did a whole analysis of the Olympics scores and my opinion on it, so if I find it I attach it here. I think at the Olympics SP he could have gotten higher scores of judges would have given him deserved +5 GOEs on his godly done elements. But that would back up his score only by roughly 2-3 points. So he still wouldn't have reached the 100. I don't really have a problem with his scores at the Olympics, just in comparison to other skaters, but imo the final results are fair because of the mistakes that happened to Yuzu and because I am not on the same page with ppl saying Nathan, Yuma or Shoma are that bad as skaters that even if they skate visibily better that they still have to lose against a Yuzu who made mistakes. Imo Yuzu's quality is undeniably the best of them all, but it doesn't mean the other skaters don't have any kind of qualities to be worthy medal winners.

I think there are a couple of competitions where Yuzu was underscored and in the last quad it happened more frequently or was more visible than before Olympics 2018. But contrary to some others I don't think he was underscored to the extent that he was judged completely unfairly or unreasonably, just not as good as he would have deserved. Tbf I think there are other skaters who are constantly underscored to more extreme extents, currently competing and retired than Yuzu.

Don't get me wrong I love Yuzu's skating and I always think he deserved better, it's just I can't get behind the narrative that only Yuzu was mistreated by judges, because it happens at every competition to many different skaters.

[antialiasis]

You mentioned being a part of the International Mathematical Olympiad. How did you end up doing in the tournament, and how did you get selected?

I went twice: first to Vietnam in 2007, where I got 6 points on one of the problems, and then to Spain in 2008, where I could have easily gotten full marks on a problem but because I forgot to prove a trivial edge case I ended up with four, which was a bummer. (The IMO is structured with six problems, three per day, with each one worth seven points, and you have 4.5 hours per day to solve them; the first problem each day is the easiest and the third the hardest.)

In both cases I believe I was in the middle of the Icelandic team, scoring-wise. As usual, Iceland is a tiny country, so when you pick the six best high-school-aged Icelanders at a thing they aren’t going to be great on a global scale. The first time I went, there was one guy who was a real supergenius on an Icelandic scale, who I think got a bronze medal (half of the participants get either gold, silver or bronze), which is a rarity for us. (Same guy was also a talented pianist and played in youth league football tournaments; the kind of guy you just sort of look at and go ‘Yeah, he is just going to be better than me at literally anything.’) If I recall correctly Iceland had won one or two silver medals at the IMO ever (and zero golds). Don’t know if there have been more by now.

The selection was done via two levels of math tournaments, one with more, easier problems and then, for the top 25 scorers on that, a second one with fewer, more IMO-like (but still easier than the real thing) problems. I think I placed something like 22nd in the first one for 2007, but much higher in the second, because I’m relatively better at that sort of problem. For 2008 I actually missed the first tournament for some reason, but they invited me to the second anyway because I’d been on the team the previous year, and again I placed in the top six. In 2009 I did take part in the first tournament again but managed to bungle it by spending too much time on one of the harder, more interesting problems instead of racking up points on the easier ones, so one way or another I didn’t make the cutoff to take part in the second one.

[cfalindia]

https://www.cfalindia.com/olympiad-exam/

[supriyawithoutsu]

🥲

[straightlightyagami]

i arrogantly believe if math olympiads were only combinatorics i could have been an imo gold medalist

[jcmarchi]

What the Launch of OpenAI’s o1 Model Tells Us About Their Changing AI Strategy and Vision

New Post has been published on https://thedigitalinsider.com/what-the-launch-of-openais-o1-model-tells-us-about-their-changing-ai-strategy-and-vision/

What the Launch of OpenAI’s o1 Model Tells Us About Their Changing AI Strategy and Vision

OpenAI, the pioneer behind the GPT series, has just unveiled a new series of AI models, dubbed o1, that can “think” longer before they respond. The model is developed to handle more complex tasks, particularly in science, coding, and mathematics. Although OpenAI has kept much of the model’s workings under wraps, some clues offer insight into its capabilities and what it may signal about OpenAI’s evolving strategy. In this article, we explore what the launch of o1 might reveal about the company’s direction and the broader implications for AI development.

Unveiling o1: OpenAI’s New Series of Reasoning Models

The o1 is OpenAI’s new generation of AI models designed to take a more thoughtful approach to problem-solving. These models are trained to refine their thinking, explore strategies, and learn from mistakes. OpenAI reports that o1 has achieved impressive gains in reasoning, solving 83% of problems in the International Mathematics Olympiad (IMO) qualifying exam—compared to 13% by GPT-4o. The model also excels in coding, reaching the 89th percentile in Codeforces competitions. According to OpenAI, future updates in the series will perform on par with PhD students across subjects like physics, chemistry, and biology.

OpenAI’s Evolving AI Strategy

OpenAI has emphasized scaling models as the key to unlocking advanced AI capabilities since its inception. With GPT-1, which featured 117 million parameters, OpenAI pioneered the transition from smaller, task-specific models to expansive, general-purpose systems. Each subsequent model—GPT-2, GPT-3, and the latest GPT-4 with 1.7 trillion parameters—demonstrated how increasing model size and data can lead to substantial improvements in performance.

However, recent developments indicate a significant shift in OpenAI’s strategy for developing AI. While the company continues to explore scalability, it is also pivoting towards creating smaller, more versatile models, as exemplified by ChatGPT-4o mini. The introduction of ‘longer thinking’ o1 further suggests a departure from the exclusive reliance on neural networks’ pattern recognition capabilities towards sophisticated cognitive processing.

From Fast Reactions to Deep Thinking

OpenAI states that the o1 model is specifically designed to take more time to think before delivering a response. This feature of o1 seems to align with the principles of dual process theory, a well-established framework in cognitive science that distinguishes between two modes of thinking—fast and slow.

In this theory, System 1 represents fast, intuitive thinking, making decisions automatically and intuitively, much like recognizing a face or reacting to a sudden event. In contrast, System 2 is associated with slow, deliberate thought used for solving complex problems and making thoughtful decisions.

Historically, neural networks—the backbone of most AI models—have excelled at emulating System 1 thinking. They are quick, pattern-based, and excel at tasks that require fast, intuitive responses. However, they often fall short when deeper, logical reasoning is needed, a limitation that has fueled ongoing debate in the AI community: Can machines truly mimic the slower, more methodical processes of System 2?

Some AI scientists, such as Geoffrey Hinton, suggest that with enough advancement, neural networks could eventually exhibit more thoughtful, intelligent behavior on their own. Other scientists, like Gary Marcus, argue for a hybrid approach, combining neural networks with symbolic reasoning to balance fast, intuitive responses and more deliberate, analytical thought. This approach is already being tested in models like AlphaGeometry and AlphaGo, which utilize neural and symbolic reasoning to tackle complex mathematical problems and successfully play strategic games.

OpenAI’s o1 model reflects this growing interest in developing System 2 models, signaling a shift from purely pattern-based AI to more thoughtful, problem-solving machines capable of mimicking human cognitive depth.

Is OpenAI Adopting Google’s Neurosymbolic Strategy?

For years, Google has pursued this path, creating models like AlphaGeometry and AlphaGo to excel in complex reasoning tasks such as those in the International Mathematics Olympiad (IMO) and the strategy game Go. These models combine the intuitive pattern recognition of neural networks like large language models (LLMs) with the structured logic of symbolic reasoning engines. The result is a powerful combination where LLMs generate rapid, intuitive insights, while symbolic engines provide slower, more deliberate, and rational thought.

Google’s shift towards neurosymbolic systems was motivated by two significant challenges: the limited availability of large datasets for training neural networks in advanced reasoning and the need to blend intuition with rigorous logic to solve highly complex problems. While neural networks are exceptional at identifying patterns and offering possible solutions, they often fail to provide explanations or handle the logical depth required for advanced mathematics. Symbolic reasoning engines address this gap by giving structured, logical solutions—albeit with some trade-offs in speed and flexibility.

By combining these approaches, Google has successfully scaled its models, enabling AlphaGeometry and AlphaGo to compete at the highest level without human intervention and achieve remarkable feats, such as AlphaGeometry earning a silver medal at the IMO and AlphaGo defeating world champions in the game of Go. These successes of Google suggest that OpenAI may adopt a similar neurosymbolic strategy, following Google’s lead in this evolving area of AI development.

o1 and the Next Frontier of AI

Although the exact workings of OpenAI’s o1 model remain undisclosed, one thing is clear: the company is heavily focusing on contextual adaptation. This means developing AI systems that can adjust their responses based on the complexity and specifics of each problem. Instead of being general-purpose solvers, these models could adapt their thinking strategies to better handle various applications, from research to everyday tasks.

One intriguing development could be the rise of self-reflective AI. Unlike traditional models that rely solely on existing data, o1’s emphasis on more thoughtful reasoning suggests that future AI might learn from its own experiences. Over time, this could lead to models that refine their problem-solving approaches, making them more adaptable and resilient.

OpenAI’s progress with o1 also hints at a shift in training methods. The model’s performance in complex tasks like the IMO qualifying exam suggests we may see more specialized, problem-focused training. This ability could result in more tailored datasets and training strategies to build more profound cognitive abilities in AI systems, allowing them to excel in general and specialized fields.

The model’s standout performance in areas like mathematics and coding also raises exciting possibilities for education and research. We could see AI tutors that provide answers and help guide students through the reasoning process. AI might assist scientists in research by exploring new hypotheses, designing experiments, or even contributing to discoveries in fields like physics and chemistry.

The Bottom Line

OpenAI’s o1 series introduces a new generation of AI models crafted to address complex and challenging tasks. While many details about these models remain undisclosed, they reflect OpenAI’s shift towards deeper cognitive processing, moving beyond mere scaling of neural networks. As OpenAI continues to refine these models, we may enter a new phase in AI development where AI performs tasks and engages in thoughtful problem-solving, potentially transforming education, research, and beyond.