January 2026

How I Turned ChatGPT into My Personal Mentor

How I Turned ChatGPT into My Personal Mentor

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For months, I treated ChatGPT like a search engine. It gave answers but never guidance. Every time I got stuck, I had to re-explain myself: who I am, what I do, and what I’m trying to achieve. The advice was always generic, shallow, and often wasted my time. Then I realized the problem wasn’t ChatGPT. It was how I was using it. Once I changed that, ChatGPT stopped being a tool for answers and became a thinking partner, a mentor […]

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Former astronaut on lunar spacesuits: "I don't think they're great right now"

Former astronaut on lunar spacesuits: “I don’t think they’re great right now”

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Crew members traveling to the lunar surface on NASA’s Artemis missions should be gearing up for a grind. They will wear heavier spacesuits than those worn by the Apollo astronauts, and NASA will ask them to do more than the first Moonwalkers did more than 50 years ago. The Moonwalking experience will amount to an “extreme physical event” for crews selected for the Artemis program’s first lunar landings, a former NASA astronaut told a panel of researchers, physicians, […]

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MongoDB vs ScyllaDB: Architecture Comparison

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benchANT compares MongoDB and ScyllaDB  architectures, with a focus on what the differences mean for performance and scalability When choosing a NoSQL database, the options can be overwhelming. One of the most popular choices is MongoDB, known for its easy use. But the highly performance-oriented ScyllaDB is one of the rising challengers. This benchANT report takes a closer technical look at both databases – comparing their architectures from an independent, technical angle. Both MongoDB and ScyllaDB promise a high-available, performant […]

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How Mixin Built a $1 Trillion Volume Crypto Wallet That Prioritizes Privacy Over Profit

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Crypto wallets often force users to choose between security, privacy, and usability. Since 2017, Mixin Messenger has been quietly building a different paradigm. With over $1 billion in assets under management and support for 2,900+ assets across 42 blockchains, the platform represents a contrarian bet: that users shouldn’t have to sacrifice self-custody for a Web2-like experience. Today, we sit down with Sonny Liu, CMO at Mixin, to understand how they’re rethinking the relationship between social communication, asset privacy, […]

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Why “Obvious” Performance Optimizations Often Backfire: Lessons From Systems Serving 50M+ Requests

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Theoretical optimizations can backfire in practice. We learned this the hard way at DoorDash when a “smart” HashMap change made latency worse. After years optimizing 50M+ monthly requests, here’s what actually works: measure tail latencies not averages, layer your caching with jittered TTLs, profile real workloads instead of trusting Big O, and treat performance as a practice not a project. Your intuition about what’s slow might probably be wrong.

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Prototyping a Real-Time Product Recommender using Contextual Bandits

Prototyping a Real-Time Product Recommender using Contextual Bandits

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Hi everyone, I am writing a blog series on implementing real-time recommender systems. Part 1 covers the theoretical implementation and prototyping of a Contextual Bandit system. Contextual Bandits optimize recommendations by considering the current “state” (context) of the user and the item. Unlike standard A/B testing or global popularity models, bandits update their internal confidence bounds after every interaction. This allows the system to learn distinct preferences for different contexts (e.g., Morning vs. Evening) without waiting for a […]

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A Tumor Aware DenseNet Swin Hybrid Learning with Boosted and Hierarchical Feature Spaces for Large-Scale Brain MRI Classification

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This study proposes an efficient Densely Swin Hybrid (EDSH) framework for brain tumor MRI analysis, designed to jointly capture fine grained texture patterns and long range contextual dependencies. Two tumor aware experimental setups are introduced to address class-specific diagnostic challenges. The first setup employs a Boosted Feature Space (BFS), where independently customized DenseNet and Swint branches learn complementary local and global representations that are dimension aligned, fused, and boosted, enabling highly sensitive detection of diffuse glioma patterns by […]

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Claude for Excel opens the gates

Claude for Excel opens the gates

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Read Online | Sign Up | Advertise Good morning, {{ first_name | AI enthusiasts }}. Developers got Claudepilled first, and now the spreadsheet crowd is next. Anthropic just expanded Claude for Excel access — and while Code and Cowork have dominated the hype cycle, this one lands directly in the workflows of virtually every knowledge worker on the planet. In today’s AI rundown: Anthropic expands Claude for Excel access The Rundown Roundtable: Our AI use cases Create ads […]

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Feature Leakage in Machine Learning: The Silent Killer Destroying Your Model’s Real Performance

Feature Leakage in Machine Learning: The Silent Killer Destroying Your Model’s Real Performance

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Author(s): Rohan Mistry Originally published on Towards AI. Understanding Data Leakage, Target Leakage, and Temporal Leakage — And How to Detect and Prevent Them Your machine learning model achieves 98% accuracy on validation data. Your team celebrates. You deploy to production. Source: Image by author.The article delves into the concept of data leakage in machine learning, explaining how it can lead to models performing well on training data but failing in real-world applications. It outlines three main types […]

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Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Control

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This paper presents a strictly convex chance-constrained stochastic control framework that accounts for uncertainty in control specifications such as reference trajectories and operational constraints. By jointly optimizing control inputs and risk allocation under general (possibly non-Gaussian) uncertainties, the proposed method guarantees probabilistic constraint satisfaction while ensuring strict convexity, leading to uniqueness and continuity of the optimal solution. The formulation is further extended to nonlinear model-based control using exactly linearizable models identified through machine learning. The effectiveness of the […]

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