Generative AI News
We bring to you the the latest generative AI news and trends. Generative AI breakthroughs, challenges, applications, and ethical issues.
Latest Generative AI News
Amazon announces free courses on Generative AI
The e-commerce giant is starting a program called “AI Ready” to give free AI skills training to 2 million people by 2025. They want to meet the high demand for AI experts and help workers earn more money.
The state of AI in 2023: Generative AI’s breakout year
A report from McKinsey shows that generative AI tools are quickly becoming more popular. According to the report, around one-third of the organizations surveyed use generative AI on a regular basis in at least one area of their business. 40 percent of these organizations plan to increase their investment in AI.
Introducing generative AI as a part of the core curricula
A Financial Express article suggests that teaching generative AI as a core subject in universities is essential for the future workforce. It discusses the advantages and challenges of incorporating generative AI into the academic curriculum.
GPT-5 won’t be much better than GPT-4?
Bill Gates, the former CEO and Chairman of Microsoft, said in an interview with Handelsblatt that he thinks generative AI has peaked in its features and that GPT-5, the next version of OpenAI’s large language model, will not be much better than GPT-4.
He believes its only set to undergo refinement, with no major featured being added. Read more.
Generative AI News
EV Battery Makers Betting Big on AI
According to a report by Firstpost, EV battery makers are betting big on AI to revolutionise how batteries are made. They aim to revolutionise the electrolyte materials used in batteries and, in turn, transform the energy storage landscape.
Google will protect users of Generative AI tools
Google has announced that it will protect its customers using its generative AI tools from copyright lawsuits. Cyberpunk 2077 developers used AI to recreate the voice of a deceased actor for the game.
China introduces guidelines for companies
China has introduced guidelines for companies supplying generative AI-oriented facilities, according to Cointelegraph. These guidelines seem to impose limits on data authorities utilised for AI blueprints’ preparation.
10 Biggest Generative AI Trends For 2024
Forbes reported on the 10 biggest generative AI trends for 2024, including bigger and more powerful models, electoral interference, ethical challenges, and new applications in various domains.
Get ahead of the curve with our assortment of news and guides, keeping you in the loop about the newest breakthroughs in generative AI.
Generative AI News and Updates:
Microsoft’s New AI Bug Bounty Program Has Rewards Up To $15K.
Microsoft launched a bug bounty program offering rewards up to $15,000 for finding vulnerabilities in AI systems, aiming to improve AI safety through external security testing.
Google Employees Raise Doubt About Bard
Leaked conversations among Google employees working on Bard show concerns about the chatbot’s effectiveness and the return on investment.
Legal Cases Against Generative AI
Plagiarism accusations against generative AI are not uncommon, as generative AI can create content that resembles or copies existing works without proper attribution. Here are some of the most famous legal cases against generative AI.
In January 2023, a group of software developers sued Microsoft, GitHub, and OpenAI. They claimed that Copilot, an AI system that generates code, violated their copyright. The developers alleged that Copilot used licensed code snippets without giving proper credit.
In April 2023, two companies, Stability AI and Midjourney, were sued by a group of artists. The artists claimed that these companies violated their rights by using their artwork without permission to train their AI art tools.
In May 2023, Getty Images sued Stability AI for using millions of images from its site without permission to train Artbreeder, an art-generating AI.
In July 2023, AI detection tools falsely accused some international students of cheating. The tools flagged their writing as AI-generated due to the simplicity and predictability of their word choice and sentence structure.
These are some of the most famous plagiarism accusations against generative AI. Come back for more updates and generative AI news. Subscribe today to receive email notifications for all new posts.
Define Generative AI
Generative AI is a type of artificial intelligence that can create new content or data that resembles but does not repeat the original data.
It uses machine learning models that learn the patterns and structures of the training data and then generate new examples based on them. Generative AI can produce various kinds of media, such as text, images, video, audio, code or synthetic data.
Some examples of generative AI models are Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Autoregressive models and Transformers. Generative AI has applications in creative activities, data enrichment, problem-solving and innovation in different domains.
We bring you the latest Generative AI News and Trends!
Generative AI is one of the most exciting and innovative fields of artificial intelligence, where machines can create new content such as text, images, music, and more. In this web page, you will find the latest generative AI news and trends, such as breakthroughs, challenges, applications, and ethical issues.
Learn about the different types of generative AI models, such as variational autoencoders, generative adversarial networks, and transformers.
Whether you are a researcher, a developer, or a curious enthusiast, this web page will keep you updated and informed about the fascinating world of generative AI. Don’t forget to subscribe to receive email notifications about new posts!
What are some common applications of Generative AI?
Generative AI is a branch of artificial intelligence that focuses on creating new content or data from scratch, such as images, text, music, or code. Some of the most common applications of generative AI are:
- Content creation
- Data augmentation
- Simulation and modelling
Content creation:
Generative AI can help artists, writers, designers, and developers to produce original and diverse content, such as paintings, poems, logos, games, or websites. For example, GPT-3 is a powerful language model that can generate coherent and fluent text on various topics and styles.
Data augmentation:
Generative AI can also help researchers and practitioners to enhance and expand their existing data sets, such as images, audio, or text. This can improve the performance and robustness of machine learning models, especially when the data is scarce or imbalanced. For example, StyleGAN is a generative adversarial network that can synthesize realistic and diverse faces from a latent space.
Simulation and modelling:
Generative AI can also help scientists and engineers to simulate and model complex phenomena, such as climate change, drug discovery, or quantum physics. This can enable faster and cheaper experimentation and innovation, as well as better understanding and prediction. For example, AlphaFold is a deep learning system that can predict the three-dimensional structure of proteins from their amino acid sequences.