Tags / 8 quotes from 4 sources
#machine-learning
Beyond Zero and One (Andrew Smart)
Inceptionism: neural networks dreaming psychedelic images
But why does the human brain react to LSD the way it does? And, if a machine were to achieve human-like consciousness, would it also react to “digital” LSD and enter an altered state of machine consciousness? Recently, Google’s artificial neural networks for image recognition…
DeepMind and the Gödel Machine
many of the writers cited above would point to dozens of cool AI projects, such as Jürgen Schmidhuber’s Gödel Machine, which can self-improve by writing its own code after it proves the new code is more optimal. It is a stunning model, but has yet to be really programmed…
Reinforcement learning inspired by the brain
DeepMind’s algorithm is directly inspired by theories about how the human brain stores, retrieves, and learns information—called reinforcement learning. The founder of the company, Demis Hassabis, is himself a neuroscientist who began his career as a game developer. Using…
How To Leave Academia
Data science as a way out of academia
The most accessible job to a typical physicist cum programmer goes by the job title Data Scientist. It's also one of the more high paying jobs in technology. Probably the best way to describe the job is 'be the programmer who understands regression and confidence…
Introducing Artificial Intelligence (Henry Brighton and Howard Selina)
Samuel's checkers program learns to win
As a result of learning from its experience, the program carried on improving quickly and soon beat a checkers champion. The champion remarked after defeat in 1965 …
A program can outplay its designer
This victory of machine over man is widely cited, and for good reason. It demonstrates an important lesson: the capabilities of an artificial agent are not necessarily restricted by the capabilities of the designer. Samuel’s program plays better checkers than he does.
Machine learning spans symbols and networks
Machine Learning is a branch of AI that spans both the classical symbolic approach and connectionism. Here, models of learning capture the ability of an agent to improve itself in light of information in the environment. Often, the ability of connectionist systems to learn is…
Shivon Zilis - Machine Intelligence
Machine intelligence
I mean “machine intelligence” as a unifying term for what others call machine learning and artificial intelligence. (Some others have used the term before, without quite describing it or understanding how laden this field has been with debates over descriptions.) I would have…