Why Extracting Text From PDFs Still Feels Like a Hack–And the Legacy Design that Keeps AI Stuck

Devs working with LLMs run into document parsing constantly. And every few months, there’s a new wave of hype (or frustration) around the PDF problem. During those moments, it’s not unusual to see software folks venting about how one file format became such a massive headache. But the struggle isn’t new. Long before LLMs entered … Read more

How Blockchain Is Redefining Financial Inclusion for the Unbanked in 2025

In 2025, the global economy will continue to rapidly digitize. Do you know another secret? Yet over 1.4 billion people remain unbanked, according to the latest World Bank data. These people lack access to traditional financial services due to systemic barriers, such as identity issues, geographic isolation, high service fees, and distrust in centralized institutions. … Read more

From Crisis to Security – How DePIN Can Solve Tonga’s Cybersecurity Challenges

A comprehensive response to recent data breaches and a roadmap for digital sovereignty The Wake-Up Call – Recent Cybersecurity Breaches in Tonga The recent leak of patient information online has sent shockwaves through Tonga’s government and healthcare systems, highlighting a critical vulnerability that threatens not just individual privacy, but national security itself. When hackers can … Read more

How U.S. Copyright Law Applies to LLM Training

:::tip ANDREA BARTZ, CHARLES GRAEBER, and KIRK WALLACE JOHNSON v. ANTHROPIC PBC, retrieved on June 25, 2025, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This is part 4 of 10. ::: ANALYSIS Section 107 of the Copyright Act identifies four factors for determining whether a given use … Read more

QDyLoRA in Action: Method, Benchmarks, and Why It Outperforms QLoRA

Table of Links Abstract and 1. Introduction Proposed Method: Quantized DyLoRA Experiments and Evaluation On the semi-sorted behavior of QDyLoRA Conclusion, Limitations, and References A. Supplementary Material A.1. Hyperparameters A.2. Generated Text Quality 2 Proposed Method: Quantized DyLoRA Following QLoRA (Dettmers et al., 2023), we used 4-bit Normal Float (NF4) for storing the double quantized … Read more

Beyond Static Ranks: The Power of Dynamic Quantization in LLM Fine-Tuning

:::info Authors: (1) Hossein Rajabzadeh, University of Waterloo and Huawei Noah’s Ark Lab (hossein.rajabzadeh@uwaterloo.ca); (2) Mojtaba Valipour, University of Waterloo (mojtaba.valipour@uwaterloo.ca); (3) Tianshu Zhu, Huawei Noah’s Ark Lab (tianshu.zhu@huawei.com); (4) Marzieh Tahaei, Huawei Noah’s Ark Lab (marzieh.tahaei@huawei.com); (5) Hyock Ju Kwon, (hjkwon@uwaterloo.ca); (6) Ali Ghodsi, (ali.ghodsi@uwaterloo.ca); (7) Boxing Chen, Huawei Noah’s Ark Lab (boxing.chen@huawei.com); (8) … Read more

More Than a Feeling: Visualizing Why Filter Atoms Outsmart LoRA in Fine-Tuning

Table of Links Abstract and 1. Introduction Preliminary Methods Experiments Related Works Conclusion and References Details of Experiments Additional Experimental Results 7 Details of Experiments 7.1 Details of Datasets VTAB dataset is uniquely challenging and well-suited for the evaluation of parameter-efficient tuning methods in the context of few-shot knowledge transfer. VTAB-1k encompasses a diverse range … Read more

Tuning the Pixels, Not the Soul: How Filter Atoms Remake ConvNets

Table of Links Abstract and 1. Introduction Preliminary Methods Experiments Related Works Conclusion and References Details of Experiments Additional Experimental Results 5 Related Works 5.1 Pre-training and Fine-tuning The standard practice of pre-training and fine-tuning [13,17,60,70] entails models initially undergoing pre-training on datasets such as ImageNet-21K, BookCorpus, and Common Crawl [46, 51, 79]. Subsequently, these … Read more

Keep the Channel, Change the Filter: A Smarter Way to Fine-Tune AI Models

Table of Links Abstract and 1. Introduction Preliminary Methods Experiments Related Works Conclusion and References Details of Experiments Additional Experimental Results 3 Methods In this section, we decompose convolution filters over a small set of filter subspace elements, referred to as fitler atoms. This formulation enables a new model tuning method via filter subspace by … Read more

Keep the Channel, Change the Filter: A Smarter Way to Fine-Tune AI Models

:::info Authors: (1) Wei Chen, Purdue University, IN, USA (chen2732@purdue.edu); (2) Zichen Miao, Purdue University, IN, USA (miaoz@purdue.edu); (3) Qiang Qiu, Purdue University, IN, USA (qqiu@purdue.edu). ::: Table of Links Abstract and 1. Introduction Preliminary Methods Experiments Related Works Conclusion and References Details of Experiments Additional Experimental Results Abstract. Efficient fine-tuning methods are critical to … Read more

Meet the HackerNoon Top Writers – Vladislav Guzey on Writing and Creativity

Introduction Hello! I’m Vladislav Guzey, known online as Proflead. I bring over 17 years of experience in tech, holding roles such as Web Developer, Data Director, Growth Hacker, AI Enthusiast, and Educator. My expertise lies in web development, AI, and sharing knowledge through practical tutorials and engaging content. You can find my work on my … Read more

Hyra Network Honored As “Technology Startup Of The Year” At The 2025 Globee® Awards

Dubai, United Arab Emirates, July 1st, 2025/Chainwire/–Decentralized AI Framework Gains Recognition for Expanding Access to Compute Power. The digital economy has witnessed transformative platforms that fundamentally changed resource sharing: Grab revolutionized transportation, Airbnb transformed hospitality, and Shein disrupted supply chains. Now, a Vietnamese technology company is redefining the next frontier-computational power sharing itself. Hyra Network … Read more

Shheikh.io Launches SHHEIKH Token Presale For Blockchain-Backed Real‑World Asset Investments

Zurich, Switzerland, June 30th, 2025/Chainwire/–Shheikh.io Introduces Tokenization Platform for Real-World Luxury Assets, Including Properties in Dubai, Lisbon, Rome, and Bali, as Well as High-End Vehicles and Farmland. SHHEIKH, the world’s first Ethereum‑based token powered by AI‑driven property intelligence that allows Real World Asset ownership, today opens its limited period presale. Shheikh.io, an AI-powered Web3 platform, … Read more

Mathematical Proofs for Truthful Rebate Mechanisms (TFRM)

Table of Links Abstract and 1. Introduction Related Work Preliminaries 3.1 TFMs: Desirable Properties 3.2 Groves’ Redistribution Mechanism (RM) IDEAL-TFRM: Impossibility of Achieving Strictly Positive Redistribution Index Transaction Fee Redistribution Mechanism (TFRM) R-TFRM: A TFRM Robust to Miner Manipulation 6.1 R-TFRM: Analyzing Impact of Miner Manipulation on Rebate and Miner Revenue R2-TFRM: Robust and Rational … Read more

How a College Student Built Software Behind Chicago’s Michelin-starred Restaurant

UChicago student Wes Kim helped a mushroom vendor supplying Michelin-starred restaurants automate inventory using AI—after a farmer’s market meeting. What started as a school project evolved into a real-world solution, saving hours of manual work and proving tech’s power in overlooked industries. Now he’s tackling healthcare automation next.

SquareX Reveals That Employees Are No Longer The Weakest Link, Browser AI Agents Are

Palo Alto, California, June 30th, 2025/CyberNewsWire/-Every security practitioner knows that employees are the weakest link in an organization, but this is no longer the case. SquareX’s research reveals that Browser AI Agents are more likely to fall prey to cyberattacks than employees, making them the new weakest link that enterprise security teams need to look … Read more

a16z Thinks Controversial Startup Cluely Is the Future of AI

Quick Summary Cluely, the startup promising to “cheat on everything,” just raised $15 million from a16z (Andreessen Horowitz). n The company hasn’t launched a real product yet but is already making headlines with viral content. n a16z partner Bryan Kim says speed and attentionmatter more than polished products in today’s AI world. n Cluely’s marketing may be … Read more

How an Open Model and a Pile of Data are Changing Time Series Analysis

Table of Links Abstract and 1. Introduction Related Work Methodology Experimental Setup and Results Conclusion and Future Work Acknowledgments Reproducibility statement Impact statement, and References 5. Conclusion and Future Work We release the first open-source family of time series foundation models and make contributions at all stages of the development and evaluation process. We first … Read more

When a Specialized Time Series Model Outshines General LLMs

Table of Links Abstract and 1. Introduction Related Work Methodology Experimental Setup and Results Conclusion and Future Work Acknowledgments Reproducibility statement Impact statement, and References 4. Experimental Setup and Results We extend the experimental benchmark introduced by Wu et al. (2023) across various dimensions. Below, we outline the design choices of our benchmark and highlight … Read more

How Do You Train an AI to Understand Time? With a Giant Pile of Data.

Table of Links Abstract and 1. Introduction Related Work Methodology Experimental Setup and Results Conclusion and Future Work Acknowledgments Reproducibility statement Impact statement, and References 3. Methodology We first collect a large number of public time series data into the Time Series Pile and then use it to pre-train a transformer model on the masked … Read more

Why Training on Time Series Beats Fine-Tuning LLMs for Time Series Tasks

Table of Links Abstract and 1. Introduction Related Work Methodology Experimental Setup and Results Conclusion and Future Work Acknowledgments Reproducibility statement Impact statement, and References 2. Related Work Transformers and patching for time series modeling. There is a growing body of work utilizing transformers for various time series analysis tasks (Wen et al., 2023). One … Read more