wish IRCTC were able to handle tatkal traffic better
struggled two days in a row with 'high load at the moment' message
I wonder how they are actually doing things around this
(via Arindam Khan - CS Prof at @iiscbangalore on LinkedIn) -
𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗚𝗲𝗼𝗺𝗲𝘁𝗿𝘆 𝗳𝗿𝗼𝗺 𝗮 𝗠𝗮𝘀𝘁𝗲𝗿!
Prof. Mark de Berg (TU Eindhoven) is spending his sabbatical at IISc and this week he is delivering a minicourse on topics in computational geometry and randomized algorithms. The best part? It is designed to be accessible, even if you do not have a prior background in computational geometry.
If you have ever encountered computational geometry as a student, chances are you have come across his textbook. I still remember learning from it during my undergraduate days at IIT Kharagpur almost two decades ago.
Beyond his influential research, Prof. de Berg is known as an exceptional teacher. Thus, it's an opportunity to see how a field is explained by someone who helped build it, and to experience the clarity that has inspired generations of students.
If you enjoy algorithms, geometry, or simply good teaching, this is something you should not miss.
The lectures are recorded and streamed online.
The first lecture started with Backward Analysis of Quicksort and gave a meta-algorithm for randomized incremental construction, which gives algorithms for many problems, including quicksort, intersection, point location, and convex hull.
YouTube link: https://t.co/HcV1gF5iCL
Next lecture is tomorrow at 2 pm IST.
Where others use AI to “create”, at TigerBeetle we’re more excited about how to use the machines to “destroy”.
Some see AI as a way to “type faster” or “increase productivity”, but at TigerBeetle I tell the team we’re already “too productive” (through TigerStyle), we want calm focused work not burnout… and we know that all the huge gains come from understanding anyway.
So “destruction” aka testing, i.e. as a foil or sparring training partner, is where we see it’s at with AI.
Not to create. That stays with the humans so we don’t atrophy our understanding, which is more valuable than “LOC”.
But to increase quality through defense in depth in testing. But even there, the gains with AI are marginal, a few percent, compared to the 90% power of our DST, which again, came from systems thinking.
So I encourage our team to “keep playing the violin yourself”, to keep practicing, keep training, keep investing in understanding.
Found this cool concise list of computer science laws: some of these ideas go back to the 19th century but still hold true today, great read
https://t.co/mvUb2OX5v5
I was exploring @ScyllaDB 's Monster SCALE Summit.
Really liked how they have given bylines as creators. I hope to someday have something like this and make my github username a reality XD
I reviewed an architecture document last week. It had a detailed diagram with API Gatway, Kafka, microservices, Redis, Kubernetes etc. It felt like the kind of architecture diagram you'd draw in a system design discussion.
But it had zero questions. Also, no mention of any assumptions. The architect had just drawn boxes that looked right, based on what big tech companies do. That conversation stuck with me, so I wrote about it.
Imo, architecture should start with questions, not boxes.
The post covers why good architects ask simple questions, what separates curious questions from performance questions and a checklist I use to ground architecture in actual constraints before they start drawing boxes.
Blog link - https://t.co/GlNGsVF4ud
Many database systems include compilers, meaning that your SQL query is turned into machine code.
PostgreSQL has a just-in-time compiler for queries. It is not alone, a system like ClickHouse does too.
Even the good old sqlite translates queries into its own byte code for efficient execution.
Database system engineers often claim that database engines are the most badass software you can build. And they have a point.