- AI Revolution Hub
- Posts
- 28 | AI Scientists: LLMs Can Create New Knowledge for Humanity
28 | AI Scientists: LLMs Can Create New Knowledge for Humanity
Wilson CELY
August 30, 2024
In partnership with
Our Menu :)
Actionable Tips:
Next Week
Read time: 4 Minutes
GEN AI AT WORK
The AI Scientist: When Machines Start Doing the Research
Sakana AI, a Japanese research lab, has unveiled a system that might just turn the world of scientific discovery on its head.
Meet the "AI Scientist”
Imagine a tireless researcher, working 24/7, generating novel ideas, designing experiments, writing code, analyzing results, and even penning scientific papers. Now imagine this researcher isn't human at all, but an artificial intelligence system. This is precisely what Sakana AI has created.
The AI Scientist automates the entire research lifecycle, from brainstorming to peer review. It's a development that could dramatically accelerate scientific progress across various fields, starting with machine learning itself.
The $15 Paper: Democratizing Research or Opening Pandora's Box?
One of the most striking aspects of this system is its efficiency. Each research paper produced by the AI Scientist costs approximately $15 – a figure that would make any university administrator's eyes light up. This cost-effectiveness could democratize research, allowing smaller institutions and even individuals to contribute to scientific discourse at an unprecedented scale.
However, as with any transformative technology, the AI Scientist raises important questions. Could this flood the academic world with low-quality papers? How do we ensure the integrity of research in an age of automated discovery?
The Road to AGI: Are We Witnessing the Beginning of the End?
The implications of the AI Scientist extend far beyond academia. Some AI researchers, like Leopold Ashen Briner, have long posited that automated AI research is the key to achieving Artificial General Intelligence (AGI). Briner's "Situational Awareness" paper suggests we might reach this milestone as soon as 2027.
With the AI Scientist, we may be witnessing the first steps towards this intelligence explosion. As these systems improve and iterate upon themselves, we could be entering an era of exponential growth in AI capabilities.
Not Without Its Flaws: The Current Limitations
Despite its impressive capabilities, the AI Scientist is not without limitations. It currently lacks vision capabilities, sometimes produces unreadable plots, and occasionally makes critical errors in data interpretation. These flaws serve as a reminder that while AI is advancing rapidly, it still requires human oversight and refinement.
The Ethical Quandary: Potential Misuse and Unintended Consequences
As with any powerful tool, the AI Scientist comes with potential risks. There are concerns about its misuse in creating unethical research or even dangerous materials if given access to physical laboratories. The academic community will need to grapple with these ethical considerations as the technology advances.
The Future of Science: Collaboration, Not Replacement
While the AI Scientist represents a significant leap forward, it's unlikely to replace human scientists entirely. Instead, we're likely to see a shift in the role of human researchers, moving towards higher-level direction, interpretation, and ethical oversight of AI-driven research.
The Bottom Line: A New Era of Discovery
The AI Scientist represents more than just a new tool in the researcher's toolkit. It's a harbinger of a new era in scientific discovery, one where the boundaries of human knowledge could expand at an unprecedented rate. As we stand on the brink of this new frontier, one thing is clear: the future of science is set to be more exciting, more productive, and more automated than ever before.
As we navigate this brave new world of AI-driven discovery, we must remain vigilant about the ethical implications and potential risks. But if managed correctly, the AI Scientist could usher in a golden age of innovation, democratizing research and accelerating our understanding of the world around us.
The question now is not whether AI will transform scientific research, but how quickly and how profoundly. As we watch this revolution unfold, one thing is certain: the world of tomorrow will be shaped by the AI Scientists of today.
GEN AI AT WORK
Eric Schmidt Drops AI Truth Bombs
In a candid interview at Stanford, former Google CEO Eric Schmidt didn't pull any punches. From predicting the next AI revolution to calling out Europe's tech struggles, Schmidt's insights offer a glimpse into the future of tech - and it's not all rosy.
The Trillion-Dollar AI Trifecta
Schmidt believes we're on the cusp of an AI revolution, driven by three key advancements:
Massive Context Windows: Imagine an AI that's always up-to-date on current events. That's the power of larger context windows, according to Schmidt.
Super-smart AI Agents: Picture an AI running chemistry experiments overnight and learning from the results. It's not science fiction - it's happening now with systems like ChroC.
Text-to-Anything: "Build me a Google competitor in 30 seconds," Schmidt hypothesizes. With advanced text-to-action capabilities, this could soon be reality.
"When these are delivered at scale," Schmidt warns, "it's going to have an impact on the world at a scale that no one understands yet."
The Global AI Race: A Two-Horse Game?
United States: Still in the lead, with Schmidt estimating a 10-year advantage in chip technology, particularly in sub-5nm chip production.
China: Playing catch-up but investing heavily. Schmidt notes they're "whopping mad" about recent US chip export restrictions.
The Dark Horses
India: Schmidt's "big swing state" in the AI race. With a deep pool of tech talent, India could be a major player if it can stem the brain drain to Silicon Valley.
Canada: A surprising mention by Schmidt as a potential AI powerhouse, thanks to its abundant hydropower for energy-hungry AI systems.
Europe: A Continent at a Crossroads
Schmidt doesn't mince words about Europe's position: "Europe is screwed up because of Brussels." But it's not a lost cause:
France: Singled out as having potential, with Schmidt praising President Macron's efforts to boost AI development.
Germany: Not seen as a major contender, despite its industrial might.
Other EU countries: Considered too small individually to make a significant impact.
The challenge for Europe? Overcoming what Schmidt sees as stifling regulations that make cutting-edge AI research difficult.
The Rest of the Pack
Japan and South Korea: Firmly in the US camp, according to Schmidt.
Taiwan: Praised for "amazing hardware" but criticized for "terrible software."
Middle East: While not a leader in AI development, Schmidt notes their potential to fund projects, though with concerns about adhering to US national security rules.
Google's Culture Shock: From 'Don't Be Evil' to 'Don't Work Late'?
In perhaps his most controversial statement, Schmidt suggested Google has lost its edge:
"Google decided that work-life balance and going home early and working from home was more important than winning."
This from the man who helped build Google into a tech behemoth. Is this the real reason behind Google's AI stumbles?
The $300 Billion Question
How much will it cost to stay ahead in AI? Schmidt throws out a staggering figure: $300 billion. And that might be conservative.
But with great power comes great responsibility. Schmidt acknowledges the challenge of regulating these powerful systems, especially when we can't always predict what they'll learn.
Startup Advice from a Tech Titan
For the entrepreneurs out there, Schmidt's advice is clear:
Use AI to prototype - fast. If you can't build it in a day, rethink your approach.
Be prepared to hustle. Schmidt points to Elon Musk's infamous work ethic as an example.
Move quickly. In the AI age, speed is everything.
The Dark Side of the AI Moon
It's not all technological utopia in Schmidt's vision. He raises red flags about:
AI-powered misinformation, especially during elections
The need for better critical thinking skills to combat fake news
Fair compensation for content creators whose work trains AI models
The risk of widening the gap between tech-rich and tech-poor nations
The Bottom Line
As the AI race heats up, one thing's clear: the finish line is still anyone's guess. But with insights like these from industry veterans like Schmidt, we're all getting a clearer view of the track ahead.
GEN AI STARTUP
What is an AI Engineer?
Originally defined the AI Engineer as a category between "ML Engineer" and "Software Engineer." Yet what we're seeing is that those boundaries are becoming blurrier.
One definition of an AI Engineer is someone who works with chains and tooling but not products or data. Yet, as the field grows, AI is impacting engineers in multiple ways:
They can use code autocomplete and general-purpose chatbots that work out of the box.
They can build LLM-enabled product features that require new frameworks and architectures (RAG, agents, etc.).
They can leverage full-fledged coding agents that automate large parts of software planning and implementation.
So, depending on your use case, it may not be as simple as working only with infrastructure and agents. A great AI Engineer is flexible enough to move up and down the stack, harnessing AI agents, digging through evals, or fine-tuning open-source models.
In the rapidly evolving world of artificial intelligence, OpenAI, a leading research laboratory, is cooking up something sweet. The San Francisco-based company is reportedly on the cusp of unveiling two new projects that could significantly advance the field: "Strawberry" and "Orion". These developments may herald a new era in machine reasoning and language understanding.
Project Strawberry, previously known in research circles as Q*, represents a significant leap in AI reasoning capabilities. Unlike current models that generate responses in real-time, Strawberry is designed to pause and "think", mimicking human cognitive processes more closely. This could prove particularly valuable in domains requiring complex problem-solving, such as mathematics and computer programming.
The potential implications are far-reaching. If successful, Strawberry could reduce the occurrence of AI "hallucinations"—instances where AI models generate plausible but incorrect information. This has been a persistent challenge in the deployment of large language models, limiting their reliability in critical applications.
Parallel to Strawberry, OpenAI is developing "Orion", intended to be their next flagship language model. In an intriguing twist of digital evolution, Orion is being trained on data generated by an advanced version of Strawberry. This recursive approach to AI development—using one AI system to train another—may offer a solution to the growing scarcity of high-quality training data, a bottleneck in advancing AI capabilities.
OpenAI's urgency in bringing these projects to fruition is understandable. The AI landscape is increasingly competitive, with well-funded rivals such as Google's DeepMind and Anthropic hot on their heels. The integration of Strawberry into ChatGPT, potentially as soon as autumn 2024, could be a strategic move to maintain OpenAI's market leadership.
However, challenges remain. The computational resources required for these advanced models are substantial, raising questions about their scalability and environmental impact. Moreover, as AI systems become more sophisticated, concerns about their societal implications and the need for robust governance frameworks grow more pressing.
As the world watches, the success of Strawberry and Orion could redefine not just what we expect from AI, but how we interact with technology at large. In the garden of artificial intelligence, it seems, strawberries may yield the sweetest fruit yet.
These cannabis gummies keep selling out in 2024
If you've ever struggled to enjoy cannabis due to the harshness of smoking or vaping, you're not alone. That’s why these new cannabis gummies caught our eye.
Mood is an online dispensary that has invented a “joint within a gummy” that’s extremely potent yet federally-legal. Their gummies are formulated to tap into the human body’s endocannabinoid system.
Although this system was discovered in the 1990’s, farmers and scientists at Mood were among the first to figure out how to tap into it with cannabis gummies. Just 1 of their rapid onset THC gummies can get you feeling right within 5 minutes!
Thank you, see you next week!
Reply