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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.
Artificial Intelligence: Facts and Myths
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Created by Mozilla Research in 2012 and now part of Linux Foundation Europe, the Servo project is an experimental rendering engine written in Rust. It combines memory safety and concurrency to create an independent, modular, and embeddable rendering engine that adheres to web standards. Stewardship of Servo moved from Mozilla Research to the Linux Foundation in 2020, where its mission remains unchanged. After some slow years, in 2023 there has been renewed activity on the project, with a roadmap now focused on improving the engine’s CSS 2 conformance, exploring Android support, and making Servo a practical embeddable rendering engine. In this presentation, Rakhi Sharma reviews the status of the project, our recent developments in 2023, our collaboration with Tauri to make Servo an easy-to-use embeddable rendering engine, and our plans for the future to make Servo an alternative web rendering engine for the embedded devices industry. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://ossna2024.sched.com/event/1aBNF/a-year-of-servo-reboot-where-are-we-now-rakhi-sharma-igalia
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Processing and Arduino
1.
Processing.org: Programming and
digital art, Arduino Juraj Bednár
2.
3.
Processing.org: project introduction
4.
Language
5.
Minimalistic approach
6.
Community
7.
What to use
it for
8.
Arduino.cc: short introduction
9.
Similar projects
10.
Demo
11.
12.
Started in 2001
at MIT (Media Lab)
13.
GNU GPL, libraries
(core.jar) are GNU LGPL
14.
Based on Java
15.
16.
17.
18.
Possibility to use
in other Java applications (when prototype becomes application)
19.
20.
You don't need
to handle exceptions
21.
Exportable to Java
Applets, which can run on web pages
22.
Portable environment, stable
API
23.
You don't need
to learn new programming language (if you know Java, you already know most of Processing. If you know Processing, you can use it and earn lots of money as Java programmer, if you want to)
24.
25.
26.
27.
Demo
28.
29.
Several books
30.
openprocessing.org
31.
processing.org/exhibition
32.
33.
Libraries
34.
35.
Audio
36.
Video
37.
Communication with devices
(Arduino)
38.
Networking
39.
File and disk
access
40.
41.
You can buy
a kit and assemble it
42.
43.
44.
Ethernet
45.
Wifi
46.
Sensors
47.
48.
49.
OpenFrameworks
50.
Lily
51.
Field
52.
53.
Create any type
of clock you want
54.
Use reference documentation
55.