> But even so, I don't think I would have been able to learn much on my own with video lectures, at least not at the start.
This was exactly my situation. Videos can give you a lot of structured, well presented information. And for MIT courses you'd get this knowledge from the very best. The problem is that no matter how well the subject matter is presented, I would hit some conceptual snag that I couldn't resolve just by repeating the sections in the video.
Now, years ago, to clear up the concepts, I would go to math stack exchange, write down exactly what I wanted to understand using mathjax and hope that someone will provide a detailed enough explanation. Most of the time I did learn from the answers, but sometimes the answer would be too succinct. In such cases there would be a need for a back and forth and stackexchange is not really designed around that usage pattern. This hassle would eventually make me give up the whole endeavor.
Now however there are LLMs. They don't need mathjax to understand what I am talking about and they are pretty good at back and forth. In the past 6 months I have gone through 2 full MIT courses with practice sheets and exams.
So I would encourage anyone who went through the route of self learning via videos and found it to be too cumbersome and lacking to give it another go with your favorite LLM.
I spent a good minute looking at the exponential in graph, ignoring all the actual data points, thinking to myself that the experiment does show an exponential relation. Where's the lie?
I'll tell you my experience as someone who's been using Math Academy for past 6 months.
Math Academy does what every good application or service does. Make things convenient. That's it. No juggling heavy books or multiple tabs of PDFs. Each problem comes with detailed solution so getting them wrong doesn't mean looking around on the internet for a hint about your mistake (this is pre ChatGPT era of course, where not getting something correct meant putting down MathJax on stackexchange).
> better than just prompting ChatGPT/Claude/etc
The convenience means you are doing the most important part of learning maths with most ease: problem solving and practice. That is something an LLM will not be able to help you with. For me, solving problems is pretty much the only way to mostly wrap my head around the topic.
I say mostly because LLMs are amazing at complementing Math Academy. Any time I hit a conceptual snag, I run off to ChatGPT to get more clarity. And it works great.
So in my opinion, Math Academy alone is pretty good. Even great for school level maths I'd say. Coupled with ChatGPT the package becomes a pretty solid teaching medium.
> the fact is that less people take the IIT-JEET (a couple of hundred thousand), than some of our exams here - like for law school and medical school
Do you have some source backing this up? A cursory search reveals that more than 850,000 applicants attempted the IIT-JEE exam in 2023. Total available college vacancies slightly more than 16,000. This number would be around 5000 for the OG IITs.
For US medical colleges, for 2022-2023 admission cycle, 22,712 of the 55,188 students who applied to medical school matriculated. Perhaps these numbers belongs to a specific US region?
I would say that attempting JEE is now more or less a cultural thing. 90% of the applicants (pardon the number out of thin air) sit the exam because that's just something you do after finishing school.
Right, it is. Like I said, the figures I've pulled are from what I remember from 15 years back. Unfortunately I'm not able to find any sources with light searhcing.
I'd like to point out that there is a high possibility that there is an upward trend in reservation category cutoffs. And if it is indeed the case then I'd be the happiest.
You and I are referring to completely different scores. It is true that a candidate needs to have scored a minimum percentage of around 50-60% in their high-school/intermediate board exams (so 10th/12th standard) to be allowed to sit in the selection examination.
The cutoffs I'm talking about are dependent on overall performance of all candidates. In the link I have shared this cutoff is 18% (89/480) for reserved category students. There are more details in the article about the cutoff for reserved category students being 60% of that of general category ones. There is further elaboration on how many students have to drop off because of their poor performance. These vacant seats are rarely filled.
Also, the example I have provided are from 15 years ago, when I appeared for these exams. I'm not going to bother finding verifiable information from back then but the figures I mentioned are pretty much what I saw.
This is correct to some extant, and not just for getting education. As an example, in many competitive exams conducted by universities etc. to select students, the selection cutoff marks clearly show this pattern of intentional discriminatory admittance.
For someone belonging to "general" category, anyone designated to an upper caste, the cutoffs percentage for selection could be as high as 97-99%. For "reserved" category candidates, those from the lower castes, the cutoff can be as low as 10-20% for the same test. This means someone scoring 95% would not get get an admission offer while someone else scoring 15% would.
This reservation system is also a part of government jobs. I have seen "reserved" teaching positions being filled by candidates who score negative marks in the selection exams. But since no other type of candidate can fill the reserved position, the highest negative score gets the job.
Does this really alleviate the issues borne out of historical oppression of the lower cast, I don't know. Perhaps. Is this overall a good thing for a nation and its people? Again, I have no idea.
Data science requires a very strong mathematical background. Thee are libraries and software that do take care of some of the most complicated processes, but I don't believe someone can become a good data science engineer by always relying on such libraries/software.
Hoe rigorous is the treatment of mathematical topics in the AI course you offer?
Do you teach the concepts of probability/statistics, linear algebra and calculus required for the course, together with some testing or examination relevant to the subject material being taught? Or is your approach similar to Andrew Ng's Coursera course where he does give some introduction about the maths involved without going into details because they are not required, resulting in acquisition of, at times, half baked knowledge about core concepts.
What would you suggest as a starting point for a regular software engineer who'd like to look into this? See how everything comes together at a high level I mean? Because to someone on the outside, the field of game development appears to be very daunting.
You normally get a blue card with a period of validity, which is normally 4 years. While the blue card is valid you can freely switch between organisations within EU. The only restriction is that you cannot change the field of your work. So a software engineer can only apply for other software engineering positions.
To get a blue card you primarily need an unlimited contract. Companies do help with the process of procurement, like setting up an appointment. Once you get your blue card you also get another "green slip" that mentions your current employer along with your job role. Anytime you move to a different job, this slip needs to be updated, which is then done by your new employer.
After playing it for about 5-8 hours in the last 2 days, I'd say for a casual gamer like me, there is no perceptible latency. Even in an FPS like Destiny. But again, yesterday was the first time I played a AAA game after two years so maybe I'm just a bit rusty.
It's interesting that as a full time Go developer myself, my experience has been very different about the points you have mentioned. I personally think verbosity is good. For one, lack of verbosity catches my attention. If I am reviewing code that looks like some part of it is ignoring the error, I would try to find a reason about that error check exclusion. This also prevents errors being dropped by accident.
About overwriting, again this has never been a problem for me (as far as I can recall). Error values are very much localised in almost all Go code I have seen and written. If a function returns an error it is either immediately acted upon or returned by the caller. As such, any overwriting done at a later stage is more or less for convenience sake.
In a situation where bystander intervention might happen, I think people, especially those who are willing to intervene, may not be very conscious about cameras around them. Even more so with surveillance cameras.
From ISPA's website, one of the reasons to oppose DoH:
> User choice: An application switching to DoH should ensure that this switch does not undermine choices that have been previously made by the user. For example, if parents have decided to filter an internet connection in their home via network or local level DNS controls, these choices should not simply be ignored by the application.
If a parent is capable of filtering out internet traffic at DNS level, then they should be capable of doing the same on top of DoH.
Then, after some more vague concerns and handwaving, at the very end we have:
> User and access-network-operator support: If DoH doesn’t work or is slow, a customer’s internet access will be affected. The customer will contact their ISP, not the DoH provider, but the ISP won’t be able to fix things for them. As a minimum, any application switching to DoH should ensure that the selected resolver should provide a 24/7 user call centre reachable via low-cost/local rate telephony and an online support capability. Support for fault-diagnosis and resolution between ISP, resolver and users should also be provided.
I mean, I get that if a person is unaware of a custom DNS that some application is using they might fault ISPs for network failures due to DNS trouble, but this would happen with any DNS irrespective of DoH.
But every event, creative or otherwise, is made up of hundreds of smaller events. That complicated wall jump - 360 kill you just did used several input signals. Even if the server side AI can't predict the exact final outcome, it can definitely help with the intermediate, well known states for at least some of the input systems.
I say some but I do believe a large enough volume of data can improve the performance of this class of input/states.
This was exactly my situation. Videos can give you a lot of structured, well presented information. And for MIT courses you'd get this knowledge from the very best. The problem is that no matter how well the subject matter is presented, I would hit some conceptual snag that I couldn't resolve just by repeating the sections in the video.
Now, years ago, to clear up the concepts, I would go to math stack exchange, write down exactly what I wanted to understand using mathjax and hope that someone will provide a detailed enough explanation. Most of the time I did learn from the answers, but sometimes the answer would be too succinct. In such cases there would be a need for a back and forth and stackexchange is not really designed around that usage pattern. This hassle would eventually make me give up the whole endeavor.
Now however there are LLMs. They don't need mathjax to understand what I am talking about and they are pretty good at back and forth. In the past 6 months I have gone through 2 full MIT courses with practice sheets and exams.
So I would encourage anyone who went through the route of self learning via videos and found it to be too cumbersome and lacking to give it another go with your favorite LLM.