📨 Weekly digest: 13 2024 | AI on the edge?Let's explore the new frontier
There is no doubt that AI writing is becoming common thing | AI this week in the news; use cases; for the techies
Hello friends,
AI's stealthy invasion of scientific papers is here – over 60,000 in 2023 alone!
But is this a revolution or a recipe for research red flags?
Just because AI writes a paper doesn't guarantee groundbreaking discoveries or expose fraud. To truly leverage AI for scientific breakthroughs, we need to embrace some "contamination" of journals with AI-generated work.
But that doesn't mean throwing open the doors. We urgently need to define good AI practices in science and ramp up careful review processes.
Are we ready to harness the power of AI without drowning in a sea of machine-made mediocrity?
Now forget needing a separate writer and graphic designer for your news report. Imagine an AI that can craft a compelling story and design eye-catching visuals to match.
This is what expected with Foundational Models (GPAI). These AI systems can learn and perform a wide range of tasks, from translating scientific papers in real-time to suggesting new research avenues – all without needing specific programming for each individual job.
On the other hand, Generative AI is rapidly evolving, allowing AI to create entirely new content. From composing music that rivals human masterpieces to generating photorealistic images of fantastical creatures, this technology holds immense potential to revolutionize various fields.
This frontier promises advancements that could impact our lives in profound ways:
Personalized education: Imagine an AI tutor that tailors its approach to your unique learning style, making education more effective and engaging.
Scientific leaps: AI could analyze vast datasets, accelerating discoveries in fields like medicine and astronomy.
Next-Level entertainment: Prepare to be wowed by AI-generated interactive stories, video games, or music that adapt to your preferences in real-time.
Challenges and considerations:
As with any powerful technology, responsible development is paramount. Here are some key areas that demand our attention:
Safety and ethics: Mitigating bias in AI outputs and ensuring the authenticity of AI-generated content are crucial to building trust.
Job displacement: As AI automates tasks across industries, we need solutions for workforce transition and retraining.
Accessibility and efficiency: How can we make powerful AI models more accessible to smaller players and individuals to avoid widening the technological gap?
What do you think?
If you haven't already, you can start with our workbook, Building a data-driven organization.
I am looking forward to reading your thoughts in a comment.
Happy days,
Yael et al.
🦾 AI elsewhere on the interweb
OpenAI courts Hollywood in meetings with film studios, directors on Bloomberg
The UN adopts a resolution backing efforts to ensure artificial intelligence is safe on AP
Meta’s smart glasses are becoming artificially intelligent. We took them for a spin on New York Times
Apple is in talks to let Google Gemini power iPhone AI features on Bloomberg
Amazon bets $150 Billion on data centers required for AI boom on Bloomberg
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