The Tokyo Metropolitan Government is developing a Generative AI Platform, which will allow government employees to create AI applications to assist with their work. The Tokyo Metropolitan Government and municipal governments throughout the Japanese capital are increasingly using generative artificial intelligence in their administrative operations. To support this trend, the metropolitan government is working with GovTech Tokyo, an affiliated organization that promotes digitalization in local governments, to develop a Generative AI Platform. The system will allow government employees to create generative AI applications tailored to their specific duties. By encouraging active use of the platform, Tokyo authorities aim to boost efficiency in public services and address growing concerns over labor shortages. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Many believe that use of generative AI as a private tutor has the potential to shrink access and achievement gaps between students and schools with abundant resources versus those with fewer resources. Shrinking the gap is possible only if paid and free versions of the platforms perform with the same accuracy. In this experiment, we investigate the performance of GPT versions 3.5, 4.0, and 4o-mini on the same 16-question statistics exam given to a class of first-year graduate students. While we do not advocate using any generative AI platform to complete an exam, the use of exam questions allows us to explore aspects of ChatGPT's responses to typical questions that students might encounter in a statistics course. Results on accuracy indicate that GPT 3.5 would fail the exam, GPT4 would perform well, and GPT4o-mini would perform somewhere in between. While we acknowledge the existence of other Generative AI/LLMs, our discussion concerns only ChatGPT because it is the most widely used platform on college campuses at this time. We further investigate differences among the AI platforms in the answers for each problem using methods developed for text analytics, such as reading level evaluation and topic modeling. Results indicate that GPT3.5 and 4o-mini have characteristics that are more similar than either of them have with GPT4.

The association of social mobility with a college education has been studied since the early 1950's [1]. Although there are some indications that a college education is not as effective as it once was in helping graduates climb the social ladder [2], it is still the most reliable way of doing so. US News & World Report updated its rankings in 2023 to include social mobility [3], and many institutions of higher education are paying more attention to recruitment of first-generation college students and talented students from disadvantaged backgrounds. With the inclusion of such students in the typical college class comes some important considerations. For example, a student from difficult financial circumstances with an academic background to match the profile of any student an elite institution will have more difficulty paying for textbooks, a laptop, a smartphone, and other items that are almost essential to current college life [2]. As of November 2022, one such item that students from advantaged backgrounds will have access to that those from lower income brackets will not is ChatGPT4 [4]. It currently costs $20 per month for a subscription and has been called a "significant leap forward" compared to ChatGPT3.5 [5], which is free [6]. While use of generative AI is prohibited in some college classrooms, this is hard to police, and many students use it regardless of classroom restrictions [7]. When generative AI is allowed, there is a wide array of platforms from which students can choose.

Telecom giant Nippon Telegraph and Telephone will launch a business-use generative artificial intelligence platform in March, in an effort to catch up with foreign rivals in the fast-expanding market. The AI platform has higher Japanese language processing capabilities than ChatGPT, a widely used AI chatbot developed by U.S.-based OpenAI, NTT said earlier in the month. The new AI model, called tsuzumi, named after a Japanese hand drum used in traditional events, can read documents containing charts and diagrams. NTT said it aims for annual sales of over ¥100 billion ($670 million) in this AI platform business by 2027. "The market size will grow bigger and bigger as many companies compete with each other," NTT President Akira Shimada said during a news conference in early November.

IBM is taking on the likes of Microsoft, AWS, and Google by introducing Watsonx, a new generative AI platform, which will help enterprises design and tune large language models (LLMs) for their operational and business requirements. Watsonx comes with a suite of tools for tuning LLMs, a data store built on lakehouse architecture, and an AI governance toolkit, the company said. Watson AI is IBM's artificial intelligence engine that the company had trained on different machine learning algorithms along with question analysis, natural language processing, feature engineering, and ontology analysis. Watsonx can be seen as the evolution of Watson AI. With the Watsonx platform, the company said it is trying to meet enterprises' requirements in five areas including interacting and conversing with customers and employees, automating business workflows and internal processes, automating IT processes, protecting against threats, and tackling sustainability goals.

IBM is taking on the likes of Microsoft, AWS, and Google by introducing Watsonx, a new generative AI platform, which will help enterprises design and tune large language models (LLMs) for their operational and business requirements. Watsonx comes with a suite of tools for tuning LLMs, a data store built on lakehouse architecture, and an AI governance toolkit, the company said. Watson AI is IBM's artificial intelligence engine that the company had trained on different machine learning algorithms along with question analysis, natural language processing, feature engineering, and ontology analysis. Watsonx can be seen as the evolution of Watson AI. With the Watsonx platform, the company said it is trying to meet enterprises' requirements in five areas including interacting and conversing with customers and employees, automating business workflows and internal processes, automating IT processes, protecting against threats, and tackling sustainability goals.

US-based tech firm OpenAI's generative artificial intelligence (AI) tool, ChatGPT, will soon get an upgrade that would allow users to customise the service to their own needs and preferences, the company confirmed in a blog post on Thursday. While it is unclear as to exactly how these custom versions of ChatGPT would work, OpenAI is looking to add "more diverse views", in order to enable the generative platform to create responses that "other people may strongly disagree with". The upgrade is part of changes to the platform that will see OpenAI's engineers, researchers and reviewers make changes to address issues of bias in its responses. "We believe that AI should be a useful tool for individual people, and thus customisable by each user up to limits defined by society. Therefore, we are developing an upgrade to ChatGPT to allow users to easily customise its behaviour. This will mean allowing system outputs that other people (ourselves included) may strongly disagree with. Striking the right balance here will be challenging -- taking customisation to the extreme would risk enabling malicious uses of our technology and sycophantic AIs that mindlessly amplify people's existing beliefs," the blog post stated.

We're starting to see the very early stages of a tech stack emerge in generative artificial intelligence (AI). Hundreds of new startups are rushing into the market to develop foundation models, build AI-native apps, and stand up infrastructure/tooling. Many hot technology trends get over-hyped far before the market catches up. But the generative AI boom has been accompanied by real gains in real markets, and real traction from real companies. Models like Stable Diffusion and ChatGPT are setting historical records for user growth, and several applications have reached $100 million of annualized revenue less than a year after launch. Side-by-side comparisons show AI models outperforming humans in some tasks by multiple orders of magnitude.

Founded in 2019, San Francisco-based Synthesis AI has developed technology that generates vast quantities of photorealistic images and pixel-perfect labels to optimize computer vision training. "The world is exploding with cameras," says Synthesis AI CEO Yashar Behzadi. This is great news for AI startups that specialize in computer vision, a field of AI that trains computers to interpret elements from digital images and videos. Up to now, computer vision has relied heavily on supervised learning, in which humans label key attributes in an image and then teach computers to do the same. But to Behzadi, this method has some pretty major setbacks.