consecutive year
California's exodus isn't just billionaires -- it's regular people renting U-Hauls, too
Things to Do in L.A. Tap to enable a layout that focuses on the article. A renter drives a U-Haul in Mission Valley in 2023. This is read by an automated voice. Please report any issues or inconsistencies here . Anecdotal data suggest there is also an exodus of regular people who load their belongings into rental trucks and lug them to another state.
Exploring the change in scientific readability following the release of ChatGPT
The rise and growing popularity of accessible large language models have raised questions about their impact on various aspects of life, including how scientists write and publish their research. The primary objective of this paper is to analyze a dataset consisting of all abstracts posted on arXiv.org between 2010 and June 7th, 2024, to assess the evolution of their readability and determine whether significant shifts occurred following the release of ChatGPT in November 2022 . Four standard readability for mulas are used to calculate individual readability scores for each paper, classifying their level of readability. These scores are then aggregated by year and across the eight primary categories covered by the platform. The results show a steady annual decrease in readability, suggesting that abstracts are likely becoming increasingly complex. Additionally, following the release of ChatGPT, a significant change in readability is observed for 2023 and the analyzed months of 2024. Similar trends are found acr oss categories, with most experiencing a notable change in readability during 2023 and 2024. These findings offer insights into the broader changes in readability and point to the likely influence of AI on scientific writing.
Global Internet Freedom Declines, Aided by AI
Global internet freedom declined for a thirteenth consecutive year in 2023, partially as a result of AI being used to sow disinformation and enhance content censorship, according to a new report from U.S.-based nonprofit Freedom House. The 2023 Freedom on the Net report, published on Oct. 4, assesses the state of internet freedom in 70 countries through a comprehensive methodology examining obstacles to access, limits on content, and violations of user rights. The report found that many countries--including Myanmar, the Philippines, Costa Rica--have drastically restricted online freedoms this year. China has the lowest levels of internet freedom for the ninth consecutive year, the report said. Freedom House, established in 1941, publishes Freedom in the World and Freedom on the Net annually.
Senior Data Engineer- Telecommute Opportunity at Dataminr - New York City, United States
Dataminr puts real-time AI and public data to work for our clients, generating relevant and actionable alerts for global corporations, public sector agencies, newsrooms, and NGOs. Our real-time alerts enable tens of thousands of users at hundreds of public and private sector organizations to learn first of breaking events around the world, develop effective risk mitigation strategies, and respond with confidence as crises unfold. Dataminr is making its mark for growth and innovation, recently earning recognition on the Deloitte's Technology Fast 500 as well as the Forbes Cloud 100 for six consecutive years. We were also recognized as one of Built In's Best Companies to Work for in 2022 for the second consecutive year. Join our team and help the world manage risk in real time.
Data Analyst
Wood Mackenzie is the global leader in data, analysis and consulting across the energy, chemicals, metals, mining, power and renewables sectors. Founded in 1973, our success has always been underpinned by the simple principle of providing trusted research and advice that makes a difference to our customers. Today we have over 2,000 customers ranging from the largest global energy companies and financial institutions to governments as well as smaller market specialists. Our teams are located around the world. This enables us to stay closely connected with customers and the markets and sectors we cover.
IBM secures fifth consecutive year of AI Software Platform market share leadership, says new IDC report - Journey to AI Blog
For the fifth consecutive year, IDC ranked IBM the #1 market share leader in AI software platforms for 2019. In the IDC report, Worldwide AI Software Platforms Market Shares, 2019: The Battle Has Begun (doc #US46652020, July 2020), IDC valued the AI software platform market at USD 3.5 billion in 2019, a near-30% increase over the prior year. And despite a crowded landscape of competitors, IDC finds IBM leading the field among the largest AI platform players with an 8.8% share. While COVID-19 forces companies worldwide to reconsider business as usual, the accolades can wait; there's no time for a victory lap when work remains to accelerate the COVID-19 economic recovery with Data and AI. With IBM Watson positioned as the business world's first choice in AI software platforms, four competitive differentiators distinguish it from the competition.
Bias & Variance in Machine Learning
Linear Regression is a machine learning algorithm that is used to predict a quantitative target, with the help of independent variables that are modeled in a linear manner, to fit a line or a plane (or hyperplane) that contains the predicted data points. For a second, let's consider this to be the best-fit line (for better understanding). So, usually, points from the training data don't really lie on the best-fit line only, and that makes perfect sense because any data isn't perfect. That is why we are making predictions in the first place, and not just plotting a random line. The linear regression line cannot be curved in order to include all the training set data points, and hence is unable to capture an accurate relationship at times.
Bias & Variance in Machine Learning
Linear Regression is a machine learning algorithm that is used to predict a quantitative target, with the help of independent variables that are modeled in a linear manner, to fit a line or a plane (or hyperplane) that contains the predicted data points. For a second, let's consider this to be the best-fit line (for better understanding). So, usually, points from the training data don't really lie on the best-fit line only, and that makes perfect sense because any data isn't perfect. That is why we are making predictions in the first place, and not just plotting a random line. The linear regression line cannot be curved in order to include all the training set data points, and hence is unable to capture an accurate relationship at times.
OneConnect's Gamma Lab wins FinTech Team of the Year award at The Asset for two consecutive years
OneConnect, a leading technology-as-a-service platform serving financial institutions in China, is pleased to announce that its artificial intelligence research institute, Gamma Lab, won the FinTech Team of the Year award for its strong technical prowess, wide range of deployment scenarios across the financial sector and high-speed growth at The Asset Triple A Digital Awards 2020 held by international authoritative media The Asset. The Gamma O platform was awarded the Best Digital Financial Project for its success since launch in providing one-stop solutions that empowered financial institutions and technology service providers in connecting with each other. The Asset was founded in 1999, with its Triple A awards gaining a high level of influence and authority in Asian and international financial markets. For two consecutive years, Gamma Lab won the FinTech Team of the Year award, demonstrating OneConnect's industry leading position in both AI technology R&D and deployment. OneConnect's information extraction technology led at the international AI competition SemEval 2020, representing another world first for Gamma Lab in new AI technologies beyond the successes that the institute had achieved in terms of performance in the areas of microexpression recognition, facial action unit recognition, machine reading comprehension, natural language generation, emotion recognition and deep learning model inference.