I agree. While ai handles more of the repetitive tasks, we'll focus more on innovation of systems which require deep understanding of the fundamentals such as low level programming, physics, etc etc so we can build bci's, dyson spheres, etc etc
Blockchain development is a strangely similar field, a lot of cross over between a CPU or stack machine you could say, at least when compared to the foundations of microcontrollers, registers, memory and digital logic. I have a diploma in electronics and I find that gas optimization is a fascinating line of work
Thank you, these were my thoughts exactly. Sometimes it seems like one has to juggle a lot of things though - expertise in paper implementation, low level programming, reinforcement learning, gpu programming, domain specialty etc I wonder if one can end up chasing multiple things and catching nothing? does it all come together at a point?
Quantum machine learning is in a nascent stage Do you think in the coming decade there will be a breakout in this technology and race towards quantum machine learning ?? in true sense as we are still struggling to get to 100 qubits !!
I'm not holding my breath, honestly. Quantum computing has been a nascent technology since the 90s. It'll take a pretty big breakthrough. But that's why I'm looking into it :)
@@MachineLearningwithPhil As i am transitioning to ML and have ambition to eventually step into Robotics/AI which uses RL a lot !! your videos do help me learn thanks.
@@MachineLearningwithPhil Personally I choose C++ ,since I am going for a PhD focus on MARL(thanks to your video :)) and I know C is critical for robotic communication and low level optimization. I feel this is the right angle here but please correct me if I was wrong? Thanks!
I agree. While ai handles more of the repetitive tasks, we'll focus more on innovation of systems which require deep understanding of the fundamentals such as low level programming, physics, etc etc so we can build bci's, dyson spheres, etc etc
Blockchain development is a strangely similar field, a lot of cross over between a CPU or stack machine you could say, at least when compared to the foundations of microcontrollers, registers, memory and digital logic. I have a diploma in electronics and I find that gas optimization is a fascinating line of work
I've often wanted to learn about blockchain tech, but the list of things to learn always seems to grow.
Thank you, these were my thoughts exactly. Sometimes it seems like one has to juggle a lot of things though - expertise in paper implementation, low level programming, reinforcement learning, gpu programming, domain specialty etc I wonder if one can end up chasing multiple things and catching nothing? does it all come together at a point?
Quantum machine learning is in a nascent stage Do you think in the coming decade there will be a breakout in this technology and race towards quantum machine learning ?? in true sense as we are still struggling to get to 100 qubits !!
I'm not holding my breath, honestly. Quantum computing has been a nascent technology since the 90s. It'll take a pretty big breakthrough. But that's why I'm looking into it :)
@@MachineLearningwithPhil As i am transitioning to ML and have ambition to eventually step into Robotics/AI which uses RL a lot !! your videos do help me learn thanks.
Thanks for the tip regarding learning a new low-level language. I had the same thought and thank you for solidating that for me.
Nice. Which one are you going to pick?
@@MachineLearningwithPhil Personally I choose C++ ,since I am going for a PhD focus on MARL(thanks to your video :)) and I know C is critical for robotic communication and low level optimization. I feel this is the right angle here but please correct me if I was wrong? Thanks!
Sounds like C++ is the right choice. It's definitely more modern.
@@MachineLearningwithPhil Thanks Phil!
My thoughts exactly to the dot! And I teach this stuff for a living...
Awesome. Where / what do you teach??
@@MachineLearningwithPhil UPB in Bucharest