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Hello there! 👋 Welcome back to AI Creator. Get ready for a dose of exciting AI updates and intriguing reads. Just scroll down to dive in!
On command, AI can drive cars, write uni dissertations and it can even predict hair trends for 2024 👀...
⏰ Top 5 Headlines
🔗Link: Google's $30/month Duet AI assistant rivals Microsoft's Copilot for AI collaboration in Workspace apps, covering tasks like document summarization and creativity.
🔗Link: GM is using Google’s AI chatbot to handle simple OnStar calls.
🔗Link: Elon Musk and Mark Zuckerberg's fight plan may have stalled - but they will attend AI summit.
🔗Link: Cosmic, from Friendly Apps, uses quizzes and AI to build user profiles, providing a deep dating experience without charging for features like undoing swipes or seeing likes.
🔗Link: Poe's new desktop app lets you use all the AI chatbots in one place.
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💬 Longer reads
AI images are getting harder to spot. Google thinks it has a solution.
Google’s new tool digitally embeds watermarks not visible to the human eye onto AI-generated images. Even if an AI-generated image has been edited or manipulated, as seen here, the tool will still be able to detect the digital watermark.
Artificial intelligence-generated images are blurring the line between reality and fabrication, raising concerns as the 2024 presidential campaign heats up. The worry is that these lifelike images could be manipulated to disseminate false information. Google has unveiled a potential solution called SynthID, a tool that embeds a digital "watermark" imperceptible to humans but detectable by specially trained computers. While AI-generated deepfakes are growing in sophistication, this technology aims to curb their misuse, yet questions remain about its efficacy in an ongoing battle between AI creators and those aiming to deceive. 🔗Read more
OpenAI releases enterprise-grade version of ChatGPT
OpenAI introduces a new version of ChatGPT specifically designed for businesses, addressing concerns about data security and privacy. The enterprise-grade offering provides enhanced security measures, unlimited access to GPT-4, faster data analysis, and the capability to ask more complex questions.
Features and benefits: ChatGPT Enterprise assures companies control over their data, avoiding its use for GPT training. It enables of company data integration and advanced analytics tools. This move aims to cater to the needs of regulated industries seeking AI tools while safeguarding sensitive information.
Competition and impact: As OpenAI's enterprise solution enters the market, it competes with existing AI vendors catering to data privacy and security. The release aligns with OpenAI's shift towards catering to larger business needs and comes after the introduction of customizable GPT-3.5 for specific tasks, positioning ChatGPT Enterprise as a comprehensive offering for corporate AI requirements. 🔗Read more
Challenges to Nvidia's dominance
Challenger startups emerge: Up-and-coming startups are aiming to disrupt Nvidia's dominance in the AI chip market. These companies are taking various approaches to compete.
Diverse strategies: Startups like Modular focus on software to enable AI models on non-Nvidia hardware, while Lightmatter pioneers new chip architectures using lasers for data transfer. MatX targets specific applications like large-language models.
Innovation pathways: Analysts suggest that startups developing entirely new chip types, like Analog Inference's analog chips, could pose a greater threat to Nvidia by forcing a shift in product strategy, although challenges in changing industry standards persist.
ChatGPT plays doctor with 72% success
AI's role in medical diagnosis is debated as it achieves 72% accuracy in complex clinical decisions.
Medical community questions: Doctors are uncertain about acceptable AI success rates and real-world reliability.
Mass General Brigham study: ChatGPT's performance at 72% accuracy in clinical decision-making is showcased.
Potential impact: AI could enhance diagnosis efficiency and accuracy, crucial with rising healthcare complexity and costs.
Room for improvement: AI succeeds in early patient care but lacks in differential diagnosis; improvement needed.
Real-world transition: Gap between useful models and clinical use must be bridged with benchmarks and regulations.
Future goals: Diagnostic success rates need to reach 80-90% before AI can be widely deployed in hospitals.
Workers want AI to help with burnout
Amid concerns of automation and AI taking over jobs, a surprising trend emerges: workers actually want AI to aid them in their roles, as per recent research by freelance platform …. The study, involving 1,400 U.S. business leaders, found that 64% of C-suite respondents plan to increase hiring due to generative AI. Rather than fearing displacement, 70% of workers would delegate tasks to AI to reduce workloads, according to a Microsoft study. This shift reflects a desire for AI augmentation, a concept emphasizing skill enhancement through AI integration, as experts assert that AI can rescue workers from burnout while reshaping job landscapes. 🔗Read more