Andrew Ng, a leader in AI, shares his perspectives on the current AI landscape and emerging trends. He sees supervised learning and generative AI as the most important tools today that are enabling a flood of new applications across industries. He also discusses strategies for identifying promising opportunities, building startups, and managing risks responsibly.
The Exciting AI Opportunities in 2023 and Beyond
✨ AI is a general purpose technology like electricity that has many applications across sectors. Key tools today are supervised learning and generative AI.
💡 Most value today is from supervised learning eg. in ads, search, recommendations. But generative AI holds huge potential to grow rapidly in next 3 years.
🤔 AI adoption outside tech/internet is still early. Customization costs were high but new low-code tools can empower non-experts.
⚙️ Opportunities lie in diverse vertical use cases, not just in AI infrastructure/tools. Building valuable applications matters most.
🚀 Validating ideas quickly and partnering with subject matter experts helps build unique and defensible startups.
🤖 AI job disruption is concerning but technology and policies can help manage risks and distribute gains.
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Navigating the AI landscape - Supervised learning and generative AI hold the most promise today. Focus on valuable use cases, not hype.
Prioritizing pragmatic adoption - Low-code tools can accelerate adoption across industries. Applications matter most.
Leveraging cross-domain expertise - Partnering technical with subject matter experts efficiently unlocks promising opportunities.
Accelerating startup builds - Validating ideas early and recruiting leadership upfront speeds up startup success.
Capturing the long tail - Aggregating many vertical $5 million projects can create substantial value.
Managing disruption risks - Job impacts are real but can be mitigated with planning and re-training support.
Developing AI responsibly - Careful oversight can steer progress to benefit humanity over long horizons.