Carl Hewitt
Founder Actor Model and Inference Robustness. Designer of first logic programming language. Emeritus professor
Professor Carl Hewitt is known for his scientific work on founding the Actor model of computation and inference robustness as well as other work on foundations of Computer Science.
His concurrent work includes Project Liftoff Project for education, science, and technology to create universal Reusable Secure Intelligent Systems by 2030.
Carl blogs at professorhewitt.blogspot.com.
Past Activities
Code BEAM SF
11.30 - 12.15
Tactics and strategies for scalable robust intelligent systems
This talk is comprised of two parts: tactics and strategies.
First, tactics are discussed how to use Erlang and Elixir for implementing scalable robust concurrency as follows:
- Minimizing latency in mailboxes
- Implementing holes in a region of mutual exclusion
- Performing cleanup in order to facilitate further progress
Second, strategies are presented how to implement universal reusable secure intelligent systems in this decade. Reusable Secure Intelligent Systems (RSIS) have the following characteristics:
- Interactively acquire information from video, Web pages, hologlasses (electronic glasses with holographic-like overlays), online data bases, sensors, articles, human speech and gestures, etc
- Real-time integration of massive pervasively inconsistent information
- Close human interaction using hologlasses for interacting with the world and secure mobile communication
- Self-informative in the sense of knowing its own goals, plans, history, provenance of its information and having relevant information about its own strengths and weaknesses
- Teachable so that systems can interactively adapt in real time (instead of relying exclusively on passively attempting to find correlations among inputs)
- Reusable enabling an intelligent system to be used by other intelligent systems without having to start over from scratch
- Secure meaning that there are no easy ways to penetrate systems and/or deceive them into taking inappropriate actions
- No closed-form algorithmic solution is possible to implement the above capabilities
China is racing to develop its own indigenous universal reusable secure intelligent systems as rapidly as possible.
Liftoff is a proposed project for education, science, and technology to implement universal Reusable Secure Intelligent Systems by 2030. Education will be crucial to the success of Project Liftoff because there is an enormous talent shortage.
THIS TALK IN THREE WORDS
Scalable
Robust
Intelligent Systems
OBJECTIVES
Explain how to use Erlang and Elixir to implement future scalable robust intelligent systems.
TARGET AUDIENCE
Researchers, executives, and software engineers interested in the future of scalable robust intelligent systems.
Code Mesh LDN 2018
09.15 - 10.15
Ultraconcurrency is the future of programming
Soon we will have chips with thousands of cores with high-bandwidth interconnect. Such chips will power the next generation of Intelligent Applications.
Since message passing between Actors is the standard method to communicate, languages like Erlang are highly relevant.
Also, since processing a message within an Actor is purely functional, languages like Haskell are highly relevant. However, in current implementations, message latencies between Actors are at least an order of magnitude too slow. So we have some engineering work to do on ultra-concurrent programming languages for the new hardware.
This keynote presents principles and practices for ultra-concurrent programming.