The focus on agentic AI in 2025 must be balanced with the pursuit of local inference capabilities. Enabling large language models to run on personal devices could revolutionize AI accessibility and adoption.
Ultimately, converging multi-agent cognition, grounded in robust logical frameworks, with highly efficient models may unlock the next era of AI capabilities.
This approach can potentially address concerns about reliability and trust, paving the way for AI to reshape industries and redefine our relationship with technology.
The challenges
The explosive progress in AI has brought us face-to-face with compelling questions and challenges that could reshape our world. Here are three that keep us up at night:
The control problem: Imagine AI systems making decisions with real-world consequences, such as autonomous vehicles, medical diagnoses, and financial trading.
How do we ensure these systems remain aligned with human values and goals?
How do we prevent unintended consequences, biases, or even malicious use? Can we build in "off switches," or are we relinquishing control?
The job displacement dilemma: AI is automating tasks at an unprecedented rate. While this boosts productivity, it also threatens jobs across various sectors.
How do we prepare the workforce for this new reality?
How do we ensure the equitable distribution of wAI-generated wealth
Do we need a universal basic income or radical reskilling initiatives?
The existential threat: This one's straight out of science fiction, but some of the brightest minds grapple with it.
Could superintelligent AI pose an existential threat to humanity?
How do we ensure AI remains a tool and not a competitor?
Can we imbue AI with ethics and empathy, or is it fundamentally incompatible with human values?
These aren't easy questions, but they demand our attention. The future of AI depends on how we navigate these challenges.
Poll: What do you think was the most significant development in AI in 2024?
A) Intentional or accidental? Was the "advancement" in AI due to intentional data leakage or poor quality control?
B) The year of efficiency: Did lower parameter models truly outperform larger models in 2024, marking a shift towards efficiency?
C) Agentic AI vs. local inference: Which will have a bigger impact in 2025: Agentic AI or running large models on local devices?
D) The future of AI: Will multi-agent cognition models grounded in logic and formal systems be the next step-function change in AI?
Share this post
🚨❓Poll: What do you think was the most significant development in AI in 2024?
Share this post
What do you think was the most significant development in AI in 2024?
2024 undeniably witnessed a rise in efficiency, with smaller models rivaling the performance of their larger predecessors.
This trend, coupled with advancements in multimodal learning, has made AI applications more accessible and versatile.
Share
Leave a comment
Give a gift subscription
The focus on agentic AI in 2025 must be balanced with the pursuit of local inference capabilities. Enabling large language models to run on personal devices could revolutionize AI accessibility and adoption.
Ultimately, converging multi-agent cognition, grounded in robust logical frameworks, with highly efficient models may unlock the next era of AI capabilities.
This approach can potentially address concerns about reliability and trust, paving the way for AI to reshape industries and redefine our relationship with technology.
The challenges
The explosive progress in AI has brought us face-to-face with compelling questions and challenges that could reshape our world. Here are three that keep us up at night:
The control problem: Imagine AI systems making decisions with real-world consequences, such as autonomous vehicles, medical diagnoses, and financial trading.
How do we ensure these systems remain aligned with human values and goals?
How do we prevent unintended consequences, biases, or even malicious use? Can we build in "off switches," or are we relinquishing control?
The job displacement dilemma: AI is automating tasks at an unprecedented rate. While this boosts productivity, it also threatens jobs across various sectors.
How do we prepare the workforce for this new reality?
How do we ensure the equitable distribution of wAI-generated wealth
Do we need a universal basic income or radical reskilling initiatives?
The existential threat: This one's straight out of science fiction, but some of the brightest minds grapple with it.
Could superintelligent AI pose an existential threat to humanity?
How do we ensure AI remains a tool and not a competitor?
Can we imbue AI with ethics and empathy, or is it fundamentally incompatible with human values?
These aren't easy questions, but they demand our attention. The future of AI depends on how we navigate these challenges.
Poll: What do you think was the most significant development in AI in 2024?
A) Intentional or accidental? Was the "advancement" in AI due to intentional data leakage or poor quality control?
B) The year of efficiency: Did lower parameter models truly outperform larger models in 2024, marking a shift towards efficiency?
C) Agentic AI vs. local inference: Which will have a bigger impact in 2025: Agentic AI or running large models on local devices?
D) The future of AI: Will multi-agent cognition models grounded in logic and formal systems be the next step-function change in AI?
Looking forward to your answers and comments,Yael Rozencwajg
Share
Leave a comment
Share Wild Intelligence by Yael Rozencwajg
Previous big question
https://news.wildintelligence.xyz/p/are-we-heading-towards-a-conceptual-model-of-virtual-identities-in-virtual-worlds
AI technology has become much more powerful over the past few decades.
In recent years, it has found applications in many different domains: discover them in our AI case studies section.