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- Apple’s AI Privacy Strategy 📡
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Just actionable resources and strategies to accelerate your success in the age of AI
Headlines
Apple’s AI Privacy Strategy - Apple Intelligence introduced a unique AI architecture focused on on-device processing meaning ones data could stay within their phone itself.
WhatsApp Developing AI Avatar Generator - This feature will allow users to create personalized AI avatars in various settings, using a combination of user photos, text prompts, and Meta’s AI Llama model.
AI Manager Matches Human Performance - A study comparing the performance of an AI manager to human managers found that the AI powered manager achieved similar results, but the best outcomes came from AI and human managers working together.
Artists Flock to Glaze Amid AI Threat - Many artists are seeking tools to protect their work from being used for AI training without consent or compensation. The Glaze Project offers tools to prevent AI mimicry and even poison AI models.
Merger Frenzy in Contract Management Software -In recent months, there has been a flurry of M&A activity as established legal tech companies acquire smaller AI specialists to boost their CLM offerings.
GPT4All 3.0 - This open-source platform now allows users to chat with thousands of large language models offline, ensuring data privacy and security.
AI-Powered Search Revolution - By enabling natural language queries and providing direct answers, AI-powered search is reshaping how people seek information and how companies can deliver it.
The COAI Grant
We have launched a new grant program, designed to use AI as a tool for empowerment, providing veterans with the means to learn new technologies, make informed career decisions, and develop the skills needed to launch and lead innovative new businesses in an era of automation. Want to support? Know a vet? Share the link with them!
Research
A Harvard Business Review paper sponsored by Cloudera, Dell, and AMD, explored the nuance of adopting generative AI in business, focusing on the trade-offs between commercial and open-source large language models (LLMs).
Key Findings:
Open-source models offer transparency and flexibility, but demand significant technical expertise and infrastructure investment.
Commercial models provide convenience and superior performance, but raise concerns about data privacy and escalating costs.
A hybrid approach, combining open-source and commercial models, may offer the best balance of performance, security, and cost.
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