Denpol88
Denpol88 t1_iwunbu9 wrote
Reply to comment by themanhimself91 in Engineers designed a new nanoscale 3D printing material that can be printed at a speed of 100 mm/s by Shelfrock77
İt was written nm not mm
Denpol88 t1_iwto0fy wrote
Reply to comment by [deleted] in Engineers designed a new nanoscale 3D printing material that can be printed at a speed of 100 mm/s by Shelfrock77
100 millimeters per second
Denpol88 t1_iwh0eii wrote
Reply to My predictions for the next 30 years by z0rm
Next 15 years not 30 i think.
Denpol88 t1_iu06urg wrote
No, i have an another plan.
Denpol88 t1_itc76d5 wrote
Reply to When do you expect gpt-4 to come out? by hducug
In the first quarter of 2023 i think.
Denpol88 OP t1_itbir0k wrote
Reply to TabPFN, a new tabular data classification method that takes 1 second & yields SOTA performance (better than hyperparameter-optimized gradient boosting in 1h). by Denpol88
TabPFN is radically different from previous ML methods. It is meta-learned to approximate Bayesian inference with a prior based on principles of causality and simplicity. Here‘s a qualitative comparison to some sklearn classifiers, showing very smooth uncertainty estimates
TabPFN happens to be a transformer, but this is not your usual trees vs nets battle. Given a new data set, there is no costly gradient-based training. Rather, it’s a single forward pass of a fixed network: you feed in (Xtrain, ytrain, Xtest); the network outputs p(y_test).
TabPFN is fully learned: We only specified the task (strong predictions in a single forward pass, for millions of synthetic datasets) but not how it should be solved. Still, TabPFN outperforms decades worth of manually-created algorithms. A big step up in learning to learn
Imagine the possibilities! Portable real-time ML with a single forward pass of a medium-sized neural net (25M parameters).
TabPFN, a new tabular data classification method that takes 1 second & yields SOTA performance (better than hyperparameter-optimized gradient boosting in 1h).Denpol88 t1_it1p5mp wrote
Reply to Why do companies develop AI when they know the consequences could be disastrous? by ouaisouais2_2
Because if they don't do it they know others will do it.
Denpol88 t1_irjfwtl wrote
Reply to comment by NativeEuropeas in When do you think we'll have AGI, if at all? by intergalacticskyline
May be you are so pessimistic and can't think exponentially.
Denpol88 t1_ir6gew6 wrote
This is huge.
Denpol88 t1_ix2o4cl wrote
Reply to 2023 predictions by ryusan8989
What are your predicts about Gpt 5. When will it come ?