[2/7] I recently read an interesting paper on the topic of #AutoML. form it, I created a taxonomy of automl parameters as a quick summary of papers, and at the top level it has three parts. #AI#likeabosch#innovation#algorithms#machinelearning
[3/7] Metalearning: Process of learning from previous experience gained during applying various learning algorithms on different kinds of data, & hence reducing the needed time to learn new tasks for a model. #AI#likeabosch#algorithms#machinelearning#innovation#AutoML
[6/7] If you are further interested to know in detail about #AUtoML, refer the original paper "Automated Machine Learning: State-of-The-Art and Open Challenges" arxiv.org/abs/1906.02287
Until you appreciate what you currently have, more won’t make your life better.
2. It’s Never As Bad As You Think It Will Be
The problem with dread & fear is that it holds people back from taking on big challenges. What you will find — no matter how big or small the challenge — is that u will adapt to it.When u consciously adapt to enormous stress, u evolve.
What #AI lacks, humans can fill in.
What humans lack, who will fill in.
Dual standards of our society and human thinking. #Ethics, #fairness and other values are regulated for AI but same values for humans are not regulated.
Time to do introspection.
If humans are unable to grasp the ethics, morale and fairness values due to deep diversity of humanity, how can we ensure ethical frameworks created for #AI will be universal.
Humans have failed to uphold the values of #ethic across history and geography. Humans have used the technology to gain control and become superior. The weaponisation of #ai is inevitable. We have seen parallel cases from field of #biotech and specific case of #crispr
#antitrusthearing
Security and safety of consumer, product, partners and Algorithm is next set of questions. Again no satisfactory answers. #Algorithms#AI#security
#antitrusthearing very interesting question, how will you ensure that biases of your employees are getting in to the algorithm?
In fact research has proven that algorithms are learning not from the data but the way data was labelled and annotated. #ai#bias
#100daysoflearning#psychology
Day 18 update
Completed reading from Robert Cialdini
Started another reading from chapter 2 of Mayer’s book on Social Psychology, completed 5 pages
#100daysoflearning#psychology
Day 18 update
Key Learning
- spotlight effect is experienced when we think people are paying more attention to us then needed.
- we also suffer from illusion of transparency that our emotions are easily detectable.
#100daysoflearning#psychology
Day 19-20 update
Completed up to page 12/chapter 2 from Social psychology book by Mayers
Key Learning
- We overestimate the visibility of our social blunders and public mental slipups
- At center of our world is our sense of self
#QuantumComputing#quantum#technology#India Panel is packed with eminent and leading members from Science and Academia.
Apoorva Patel (IISc, Bangalore)
R. P. Singh (PRL, Ahmedabad)
Umakant Rapol (IISER, Pune)
Anil Prabhakar (IIT Madras)