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Teaching AI Writing: Purpose
Teaching AI Writing: Purpose
This is the first post in a series exploring how multimodal generative AI (genAI) writing tools can be applied to all stages of the writing cycle, from purpose through to publication. The six stage…
·leonfurze.com·
Teaching AI Writing: Purpose
Learnics - Digital Learning, Transformed
Learnics - Digital Learning, Transformed
Learnics supports your school’s shift to digital learning by revealing student online experiences to improve teaching and learning.
·learnics.com·
Learnics - Digital Learning, Transformed
Generative AI in a Nutshell - how to survive and thrive in the age of AI
Generative AI in a Nutshell - how to survive and thrive in the age of AI
Basically a full day AI course crammed into 18 mins of drawing & talking. Target audience: Everyone. Covers questions like What is generative AI, how does it work, how do I use it, what are some of the risks & limitations. Also covers things like autonomous agents, the role of us humans, prompt engineering tips, AI-powered product development, origin of ChatGPT, different types of models, and some tips about mindset around this whole thing. Here is the full drawing: https://blog.crisp.se/wp-content/uploads/2024/01/generative-AI-in-a-nutshell.png
·youtube.com·
Generative AI in a Nutshell - how to survive and thrive in the age of AI
AI Course Creator
AI Course Creator
An AI Course Creator which makes it easy to create a course with AI in minutes. Try Coursebox, the best AI Course Generator to build an online course with AI for free today.
·coursebox.ai·
AI Course Creator
Text - H.R.6466 - 118th Congress (2023-2024): AI Labeling Act of 2023
Text - H.R.6466 - 118th Congress (2023-2024): AI Labeling Act of 2023
Text for H.R.6466 - 118th Congress (2023-2024): AI Labeling Act of 2023
IN THE HOUSE OF REPRESENTATIVES November 21, 2023 Mr. Kean of New Jersey introduced the following bill; which was referred to the Committee on Energy and Commerce, and in addition to the Committee on Science, Space, and Technology, for a period to be subsequently determined by the Speaker, in each case for consideration of such provisions as fall within the jurisdiction of the committee concerned A BILL To require disclosures for AI-generated content, and for other purposes. Be it enacted by the Senate and House of Representatives of the United States of America in Congress assembled, SECTION 1. Short title.This Act may be cited as the “AI Labeling Act of 2023”. SEC. 2. Disclosures for AI-generated content. (a) Consumer disclosures.— (1) IMAGE, VIDEO, AUDIO, OR MULTIMEDIA AI-GENERATED CONTENT.— (A) IN GENERAL.—Each generative artificial intelligence system that, using any means or facility of interstate or foreign commerce, produces image, video, audio, or multimedia AI-generated content shall include on such AI-generated content a clear and conspicuous disclosure that meets the requirements of subparagraph (B). (B) DISCLOSURE REQUIREMENTS.—A disclosure required under subparagraph (A) shall meet each of the following criteria: (i) The disclosure shall include a clear and conspicuous notice, as appropriate for the medium of the content, that identifies the content as AI-generated content. (ii) The output's metadata information shall include an identification of the content as being AI-generated content, the identity of the tool used to create the content, and the date and time the content was created. (iii) The disclosure shall, to the extent technically feasible, be permanent or unable to be easily removed by subsequent users. (2) TEXT AI-GENERATED CONTENT.—Each artificial intelligence system that, using any means or facility of interstate or foreign commerce, produces text AI-generated content (including through an artificial intelligence chatbot) shall include a clear and conspicuous disclosure that identifies the content as AI-generated content and that is, to the extent technically feasible, permanent or unable to be easily removed by subsequent users. (3) OTHER OBLIGATIONS.— (A) DEVELOPERS OF GENERATIVE ARTIFICIAL INTELLIGENCE SYSTEMS.—Any entity that develops a generative artificial intelligence system shall implement reasonable procedures to prevent downstream use of such system without the disclosures required under this section, including by— (i) requiring by contract that end users and third-party licensees of the system refrain from removing any required disclosure; (ii) requiring certification that end users and third-party licensees will not remove any such disclosure; and (iii) terminating access to the system when the entity has reason to believe that an end user or third-party licensee has removed the required disclosure. (B) THIRD-PARTY LICENSEES.—Any third-party licensee of a generative artificial intelligence system shall implement reasonable procedures to prevent downstream use of such system without the disclosures required under this section, including by— (i) requiring by contract that users of the system refrain from removing any required disclosure; (ii) requiring certification that end users will not remove any such disclosure; and (iii) terminating access to the system when the third-party licensee has reason to believe that an end user has removed the required disclosure. (4) ENFORCEMENT BY THE COMMISSION.— (A) UNFAIR OR DECEPTIVE ACTS OR PRACTICE.—A violation of this subsection shall be treated as a violation of a rule defining an unfair or deceptive act or practice under section 18(a)(1)(B) of the Federal Trade Commission Act (15 U.S.C. 57a(a)(1)(B)). (B) POWERS OF THE COMMISSION.— (i) IN GENERAL.—The Commission shall enforce this subsection in the same manner, by the same means, and with the same jurisdiction, powers, and duties as though all applicable terms and provisions of the Federal Trade Commission Act (15 U.S.C. 41 et seq.) were incorporated into and made a part of this subsection. (ii) PRIVILEGES AND IMMUNITIES.—Any person who violates this subsection or a regulation promulgated thereunder shall be subject to the penalties and entitled to the privileges and immunities provided in the Federal Trade Commission Act (15 U.S.C. 41 et seq.). (iii) AUTHORITY PRESERVED.—Nothing in this Act shall be construed to limit the authority of the Commission under any other provision of law. (b) AI-Generated Content Consumer Transparency Working Group.— (1) ESTABLISHMENT.—Not later than 90 days after the date of enactment of this section, the Director of the National Institute of Standards and Technology (in this section referred to as the “Director”), in coordination with the heads of other relevant Federal agencies, shall form a working group to assist platforms in identifying AI-generated content. (2) MEMBERSHIP.—The working group shall include members from the follow
·congress.gov·
Text - H.R.6466 - 118th Congress (2023-2024): AI Labeling Act of 2023
Sourcely | Find Academic Sources with AI
Sourcely | Find Academic Sources with AI
AI-powered literature sourcing tool that quickly retrieves relevant texts based on user input. With advanced natural language processing techniques, it provides easy access to diverse information sources, saving time and effort. Get help from Sourcely AI.
·sourcely.net·
Sourcely | Find Academic Sources with AI
Researchers from Stanford and OpenAI Introduce 'Meta-Prompting': An Effective Scaffolding Technique Designed to Enhance the Functionality of Language Models in a Task-Agnostic Manner
Researchers from Stanford and OpenAI Introduce 'Meta-Prompting': An Effective Scaffolding Technique Designed to Enhance the Functionality of Language Models in a Task-Agnostic Manner
Language models (LMs), such as GPT-4, are at the forefront of natural language processing, offering capabilities that range from crafting complex prose to solving intricate computational problems. Despite their advanced functionalities, these models need fixing, sometimes yielding inaccurate or conflicting outputs. The challenge lies in enhancing their precision and versatility, particularly in complex, multi-faceted tasks. A key issue with current language models is their occasional inaccuracy and limitation in handling diverse and complex tasks. While these models excel in many areas, their efficacy could improve when confronted with tasks that demand nuanced understanding or specialized knowledge beyond their general capabilities.
·marktechpost.com·
Researchers from Stanford and OpenAI Introduce 'Meta-Prompting': An Effective Scaffolding Technique Designed to Enhance the Functionality of Language Models in a Task-Agnostic Manner