· ai
The AI Bubble Will Pop — And Why That Doesn’t Matter
How history’s biggest tech bubble explains where AI is headed next The post The AI Bubble Will Pop — And Why That Doesn’t Matter appeared first on Towards Data...
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- · ai
[Paper] Algorithm-hardware co-design of neuromorphic networks with dual memory pathways
Spiking neural networks excel at event-driven sensing yet maintaining task-relevant context over long timescales. However building these networks in hardware re...
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AI Pulse: The First Agentic Cyber Week
In 2025, AI bots officially entered Cyber Week. Learn how agents shaped traffic and shopper intent — and why retailers must optimize for AI-driven commerce....
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How to Create an ML-Focused Newsletter
Learn how to make a newsletter with AI tools The post How to Create an ML-Focused Newsletter appeared first on Towards Data Science....
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[Paper] AutoICE: Automatically Synthesizing Verifiable C Code via LLM-driven Evolution
Automatically synthesizing verifiable code from natural language requirements ensures software correctness and reliability while significantly lowering the barr...
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[Paper] How Do LLMs Fail In Agentic Scenarios? A Qualitative Analysis of Success and Failure Scenarios of Various LLMs in Agentic Simulations
We investigate how large language models (LLMs) fail when operating as autonomous agents with tool-use capabilities. Using the Kamiwaza Agentic Merit Index (KAM...
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Optimizing PyTorch Model Inference on CPU
Flyin’ Like a Lion on Intel Xeon The post Optimizing PyTorch Model Inference on CPU appeared first on Towards Data Science....
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OSpark: The All-Round Free AI Assistant Powered by MiroMind’s Open-Source MiroFlow Framework
Today marks an exciting milestone in the world of accessible AI: the official launch of OSpark, a free, all‑in‑one AI assistant designed to simplify work, creat...
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Best AI Background Generator for 2025: Create Custom Backgrounds Instantly
Introduction The demand for an advanced AI Background Generator has grown quickly as creators, brands, and e‑commerce sellers look for faster ways to design vi...
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[Paper] KAN-Dreamer: Benchmarking Kolmogorov-Arnold Networks as Function Approximators in World Models
DreamerV3 is a state-of-the-art online model-based reinforcement learning (MBRL) algorithm known for remarkable sample efficiency. Concurrently, Kolmogorov-Arno...
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[Paper] Do LLMs Trust the Code They Write?
Despite the effectiveness of large language models (LLMs) for code generation, they often output incorrect code. One reason is that model output probabilities a...
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[Paper] From sparse recovery to plug-and-play priors, understanding trade-offs for stable recovery with generalized projected gradient descent
We consider the problem of recovering an unknown low-dimensional vector from noisy, underdetermined observations. We focus on the Generalized Projected Gradient...