New York attorney and writer Alexander Zubatov weighs in on how A.I. is rapidly changing society and says he's concerned about A.I. being used as a weapon against descent on'The Ingraham Angle.' The popular artificial intelligence bot ChatGPT was forced to admit that global warming has flattened in recent years after asserting there has been an increase in temperatures. Junk Science founder Steve Milloy published a lengthy exchange he had with ChatGPT beginning with the simple question, "Is CO2 warming a hoax?" ChatGPT was quick to say "no," telling Milloy, "It is widely accepted scientific fact" that human activity has fueled CO2 emission into Earth's atmosphere. "But why has there been no global warming since 2015 despite 500 billion tons of emissions?" OpenAI ChatGPT seen on mobile with AI Brain seen on screen.

Given that China already bans Google, Facebook, Twitter, and a host of foreign news websites (including time.com) In fact, ChatGPT parent company OpenAI's decision not to launch in China--Chinese and even Hong Kong phone numbers aren't permitted to sign up--appears to preempt that very fact, with the San Francisco-based firm telling Reuters that "conditions in certain countries make it difficult or impossible" to operate. Read More: Why China, Russia's Biggest Backer, Now Says It Wants to Broker Peace in Ukraine Nevertheless, canny Chinese netizens have found numerous workarounds to access the revolutionary service, such as using virtual private networks and an overseas friend's phone number; purchasing logins via online marketplace Taobao; or simply taking advantage of a variety of proxy bots embedded in ubiquitous messaging service WeChat. Chinese social media was so abuzz with ChatGPT content this month that one AI-generated fake government notice rescinding traffic regulations sparked bedlam and a police investigation in the eastern city of Hangzhou. Unsurprisingly, China's government has now stepped in with explicit bans on WeChat hosting proxy ChatGPT services, while a strident frontpage op-ed on the perils of investing in AI-related firms (and cited ChatGPT), which published earlier this month in the state-owed Securities Times newspaper, was linked to a fall in Chinese tech stocks.

Article: 3 High-Growth AI Stocks to Back the Truck Up On Right Now - InvestorPlace Video: Here are the top AI stock picks for 2023, according to Futurum Group's Daniel Newman - CNBC Television Artificial Intelligence is on fire right now. And, so are Artificial Intelligence-related stocks. How much is just smoke and how much is real potential for growth? Here are two takes on that question. Click the article link to read all about it from InvestorPlace, and click on the video link to see CNBC's take.

While societal events often impact people worldwide, a significant fraction of events has a local focus that primarily affects specific language communities. Examples include national elections, the development of the Coronavirus pandemic in different countries, and local film festivals such as the C\'esar Awards in France and the Moscow International Film Festival in Russia. However, existing entity recommendation approaches do not sufficiently address the language context of recommendation. This article introduces the novel task of language-specific event recommendation, which aims to recommend events relevant to the user query in the language-specific context. This task can support essential information retrieval activities, including web navigation and exploratory search, considering the language context of user information needs. We propose LaSER, a novel approach toward language-specific event recommendation. LaSER blends the language-specific latent representations (embeddings) of entities and events and spatio-temporal event features in a learning to rank model. This model is trained on publicly available Wikipedia Clickstream data. The results of our user study demonstrate that LaSER outperforms state-of-the-art recommendation baselines by up to 33 percentage points in MAP@5 concerning the language-specific relevance of recommended events.

We construct a corpus of Japanese a cappella vocal ensembles (jaCappella corpus) for vocal ensemble separation and synthesis. It consists of 35 copyright-cleared vocal ensemble songs and their audio recordings of individual voice parts. These songs were arranged from out-of-copyright Japanese children's songs and have six voice parts (lead vocal, soprano, alto, tenor, bass, and vocal percussion). They are divided into seven subsets, each of which features typical characteristics of a music genre such as jazz and enka. The variety in genre and voice part match vocal ensembles recently widespread in social media services such as YouTube, although the main targets of conventional vocal ensemble datasets are choral singing made up of soprano, alto, tenor, and bass. Experimental evaluation demonstrates that our corpus is a challenging resource for vocal ensemble separation. Our corpus is available on our project page (https://tomohikonakamura.github.io/jaCappella_corpus/).

Visibility underwater is challenging, and degrades as the distance between the subject and camera increases, making vision tasks in the forward-looking direction more difficult. We have collected underwater forward-looking stereo-vision and visual-inertial image sets in the Mediterranean and Red Sea. To our knowledge there are no other public datasets in the underwater environment acquired with this camera-sensor orientation published with ground-truth. These datasets are critical for the development of several underwater applications, including obstacle avoidance, visual odometry, 3D tracking, Simultaneous Localization and Mapping (SLAM) and depth estimation. The stereo datasets include synchronized stereo images in dynamic underwater environments with objects of known-size. The visual-inertial datasets contain monocular images and IMU measurements, aligned with millisecond resolution timestamps and objects of known size which were placed in the scene. Both sensor configurations allow for scale estimation, with the calibrated baseline in the stereo setup and the IMU in the visual-inertial setup. Ground truth depth maps were created offline for both dataset types using photogrammetry. The ground truth is validated with multiple known measurements placed throughout the imaged environment. There are 5 stereo and 8 visual-inertial datasets in total, each containing thousands of images, with a range of different underwater visibility and ambient light conditions, natural and man-made structures and dynamic camera motions. The forward-looking orientation of the camera makes these datasets unique and ideal for testing underwater obstacle-avoidance algorithms and for navigation close to the seafloor in dynamic environments. With our datasets, we hope to encourage the advancement of autonomous functionality for underwater vehicles in dynamic and/or shallow water environments.

Text data can pose a risk of harm. However, the risks are not fully understood, and how to handle, present, and discuss harmful text in a safe way remains an unresolved issue in the NLP community. We provide an analytical framework categorising harms on three axes: (1) the harm type (e.g., misinformation, hate speech or racial stereotypes); (2) whether a harm is \textit{sought} as a feature of the research design if explicitly studying harmful content (e.g., training a hate speech classifier), versus \textit{unsought} if harmful content is encountered when working on unrelated problems (e.g., language generation or part-of-speech tagging); and (3) who it affects, from people (mis)represented in the data to those handling the data and those publishing on the data. We provide advice for practitioners, with concrete steps for mitigating harm in research and in publication. To assist implementation we introduce \textsc{HarmCheck} -- a documentation standard for handling and presenting harmful text in research.

Jamie Dimon, chief executive officer of JPMorgan Chase & Co., speaks virtually during a webcast ... [ ] event on a mobile phone. If you want to know which technologies will be hot in the banking industry in 2023, heed the advice of Deep Throat. In the movie All The President's Men, Woodward and Bernstein's informant--whom they refer to as Deep Throat--tells them: "Follow the money." A new study from Cornerstone Advisors, What's Going On in Banking 2023, follows the money and reveals where banks and credit unions will place their technology bets in this uncertain year. Uncertain not just because of the economic conditions, but because of the vagaries of the organizational and technological environments in which banks operate.

AI is starting to take over the Kindle Bookstore, by authors taking advantage of Kindle Direct Publishing. In the first weeks of February, over 200 e-books that listed ChatGPT as an author or co-author. These books include "How to Write and Create Content Using ChatGPT," "The Power of Homework" and poetry collection "Echoes of the Universe" and sci-fi epic about an interstellar brothel, "Galactic Pimp: Vol. There could be even thousands of new books that have been submitted in February alone, due to authors not having to disclose if they used ChatGPT or not. The vast majority of these are low quality books that are submitted to the Kindle store, just to make a quick buck.

Artificial intelligence may have begun as mere fiction in books like "Frankenstein" and "Robots," but it is now very real. As technology advances, we see more and more uses for AI.