⚡︎🔋 Microsoft launched Designer app

And more: Menlo Ventures and Anthropic collaborate to create a $100 million fund

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🚀 Here’s what’s going on today in the AI space…

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Samsung is set to acquire the UK-based startup Oxford Semantic Technologies, which specializes in knowledge graph technologies. This acquisition aims to enhance Samsung's AI capabilities across its consumer devices by integrating Oxford Semantic Technologies' AI reasoning engine, RDFox, which processes organizational data for improved user experiences. RDFox is notable for its applications in medical diagnosis, autonomous vehicle safety, financial crime detection, and product configuration recommendations. This move will allow Samsung to provide more personalized services across its product range while maintaining data security on devices. Read more

Menlo Ventures and Anthropic are collaborating to create a $100 million fund, named "the Anthology Fund," to invest in early-stage AI startups. This partnership builds on Menlo Ventures' recent major investment in Anthropic. The fund will focus on supporting startups that utilize Anthropic's AI models or are broadly AI-focused, providing initial investments starting at $100,000 and offering $25,000 in credits for using Anthropic’s models. The fund is now open for applications, aiming to streamline the investment process for promising AI ventures. Read more

Microsoft has officially launched its AI-powered Designer app, now available on iOS and Android. The app, similar to Canva, enables users to generate images and designs using text prompts for various creations like stickers, greeting cards, and collages. Designer supports over 80 languages and integrates with Microsoft Word and PowerPoint through the Copilot service, enhancing document visuals. Future updates will include features like background replacement for images. Read more

📔#1 Insights Today on AI. Click the Links to Read

As AI usage increases, concerns about embedded human biases in AI systems rise. Real-world examples show that biased data and algorithms can amplify negative effects at scale. Companies aim to tackle AI bias to ensure fairness and better results, but it's challenging. McKinsey authors note that biases stay embedded due to the need for deep data-science mastery and understanding of social forces.

AI bias refers to systems producing biased results reflecting societal inequalities. This bias can arise from training data, algorithms, or cognitive biases in data selection. For instance, facial recognition AI trained predominantly on white faces may struggle with people of color. Similarly, biased hiring algorithms might favor certain genders based on vocabulary used in resumes.

Real-life examples include healthcare AI showing lower accuracy for black patients, biased hiring systems, and predictive policing tools reinforcing racial profiling. Addressing bias involves AI governance, creating policies to guide AI development responsibly. Practices include ensuring compliance, building trust, maintaining transparency, and striving for fairness.

IBM emphasizes the importance of trusted AI, secure access, and data privacy in AI deployment. Through AI governance, companies can mitigate bias and foster ethical AI use. Identifying and managing AI bias is essential for equitable and trustworthy AI systems.

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