If you're eager to use ChatGPT for work, you might soon have the option. OpenAI has shared a waitlist for a experimental ChatGPT Professional service that, for a fee, would effectively remove the limits on the popular chatbot. The AI tool would always be available, with no throttling and as many messages as necessary. The startup hasn't said when the pilot program might launch, and it's asking would-be participants for feedback on pricing. As TechCrunch notes, the company said on its Discord server that it's "starting to think" about how it will make money from ChatGPT and keep the technology viable in the "long-term."

It mentions that as AI technology advances, new ethical considerations arise; hence we need to re-evaluate our approach to governing AI. The blog post suggests several ways of governing AI, such as regulation, industry standards, and self-regulation. It also emphasizes the importance of monitoring the development and usage of AI models like GPT-3 to ensure it's fine-tuned and trained on diverse and unbiased data.

Jan 10 (Reuters) - Microsoft Corp (MSFT.O) is in talks to invest $10 billion in ChatGPT-owner OpenAI as part of funding that will value the firm at $29 billion, Semafor reported on Monday, citing people familiar with the matter. The news underscores rising interest in the artificial intelligence company, whose chatbot has dazzled amateurs and industry experts with its ability to spit out haikus, debug code and answer questions while imitating human speech. The funding could also include other venture firms and documents sent to prospective investors outlining its terms indicated a targeted close by the end of 2022, according to the report. Microsoft declined to comment, while OpenAI did not immediately respond to Reuters requests for comment. The software giant had in 2019 invested $1 billion in OpenAI, founded by Elon Musk and Sam Altman.

ChatGPT is the application of the future – a tipping point in the technology states Harward Business Review. Ever since it made its debut, it is garnering tremendous attention for its capability to perform a variety of tasks right from responding to queries to writing code. At the basic level, ChatGPT works like any other chatbot but for the quality of output it generates, it is can be considered a class apart. What about the bias and prejudice it promotes? The updated chatGPT will be capable of retaining factual correctness in the information it provides.

Microsoft is in talks to invest an additional $10 billion into ChatGPT owner OpenAI as it looks to integrate the GPT3-based chatbot into its search engine Bing, Semafor reported. In 2019, Microsoft had invested $1 billion in OpenAI to expedite efforts to further artificial general intelligence for "widely distributed economic benefits." The recent interest to invest $10 billion could be the direct result of ChatGPT's rising popularity due to its ability to respond to queries on the internet using conversational language, a vastly different approach from what Google and Bing offer currently in the way of links. The Semafor report comes days after The Information reported that Microsoft was in talks with OpenAI to increase its stake in the company, followed by a Wall Street Journal report that said OpenAI was looking to sell shares to venture capital firms at a valuation of $29 billion. Microsoft did not immediately respond to request for comment.

On Friday, Koko co-founder Rob Morris announced on Twitter that his company ran an experiment to provide AI-written mental health counseling for 4,000 people without informing them first, The Verge reports. Critics have called the experiment deeply unethical because Koko did not obtain informed consent from people seeking counseling. Koko is a nonprofit mental health platform that connects teens and adults who need mental health help to volunteers through messaging apps like Telegram and Discord. On Discord, users sign into the Koko Cares server and send direct messages to a Koko bot that asks several multiple-choice questions (e.g., "What's the darkest thought you have about this?"). It then shares a person's concerns--written as a few sentences of text--anonymously with someone else on the server who can reply anonymously with a short message of their own.

Last year saw the emergence of artificial intelligence tools (AI) that can create images, artwork, or even video with a text prompt. There were also major steps forward in AI writing, with OpenAI's ChatGPT causing widespread excitement - and fear - about the future of writing. Now just a few days into 2023, another powerful use case for AI has stepped into the limelight - a text-to-voice tool that can impeccably mimic a person's voice. Developed by Microsoft, VALL-E can take a three-second recording of someone's voice, and replicate that voice turning written words into speech, with realistic intonation and emotion depending on the context of the text. Trained with 60,000 hours worth of English speech recordings, it can deliver a speech in "zero-shot situation," which means without any prior examples or training in a specific context or situation.

Australian universities have been forced to change the way they run exams and other assessments amid fears students are using emerging artificial intelligence software to write essays. Major institutions have added new rules which state that the use of AI is cheating, with some students already caught using the software. But one AI expert has warned universities are in an "arms race" they can never win. ChatGPT, which generates text on any subject in response to a prompt or query, was launched in November by OpenAI and has already been banned across all devices in New York's public schools due to concerns over its "negative impact on student learning" and potential for plagiarism. In London, one academic tested it against a 2022 exam question and said the AI's answer was "coherent, comprehensive and sticks to the points, something students often fail to do", adding he would have to "set a different kind of exam" or deprive students of internet access for future exams. In Australia, academics have cited concerns over ChatGPT and similar technology's ability to evade anti-plagiarism software while providing quick and credible academic writing.

The global economy is increasingly dependent on knowledge workers to meet the needs of public and private organizations. While there is no single definition of knowledge work, organizations and industry groups still attempt to measure individuals' capability to engage in it. The most comprehensive assessment of capability readiness for professional knowledge workers is the Uniform CPA Examination developed by the American Institute of Certified Public Accountants (AICPA). In this paper, we experimentally evaluate OpenAI's `text-davinci-003` and prior versions of GPT on both a sample Regulation (REG) exam and an assessment of over 200 multiple-choice questions based on the AICPA Blueprints for legal, financial, accounting, technology, and ethical tasks. First, we find that `text-davinci-003` achieves a correct rate of 14.4% on a sample REG exam section, significantly underperforming human capabilities on quantitative reasoning in zero-shot prompts. Second, `text-davinci-003` appears to be approaching human-level performance on the Remembering & Understanding and Application skill levels in the Exam absent calculation. For best prompt and parameters, the model answers 57.6% of questions correctly, significantly better than the 25% guessing rate, and its top two answers are correct 82.1% of the time, indicating strong non-entailment. Finally, we find that recent generations of GPT-3 demonstrate material improvements on this assessment, rising from 30% for `text-davinci-001` to 57% for `text-davinci-003`. These findings strongly suggest that large language models have the potential to transform the quality and efficiency of future knowledge work.

Language is a multilevel symbolic system that includes multiple levels: phonetics, morphology, syntax, semantics, and pragmatics. The most basic language symbols can be combined to form more complex and endless symbol sequences to allow flexible expression of meaning. As such, language is also considered the carrier of human thought and the most natural tool through which humans exchange ideas and express emotions. Because of the diverse and flexible characteristics of language, it is difficult to study the mechanism of human language understanding and to build a computation model that can understand language. In the early days of computer science, language research pioneers attempted to conduct cross-disciplinary research in computer science, linguistics, and cognitive science. They aimed to establish connections between human language-understanding mechanisms and language-computation models [1, 2, 3, 4, 5, 6]. However, owing to the complexity of the problem, interdisciplinary research has gradually become separated over the decades, forming subfields such as natural language understanding in computer science, psycholinguistics in cognitive psychology, and neurobiology of language research in cognitive neuroscience. In this paper, "cognitive science" mainly refers to the two fields of cognitive psychology and cognitive neuroscience, particularly the branches of psycholinguistics and the cognitive neuroscience of language [7]. Figure 1 shows the relationship between cognitive and computer science in the direction of language understanding. There are substantial differences in the research questions and methods adopted in the two fields.