~hackernoon | Bookmarks (1915)

We propose a framework that uses metric distortion to study the link between topology awareness and generalization in Graph Neural Networks (GNNs). By examining how GNNs preserve structural properties in their embeddings, we reveal insights into their generalization performance, particularly in node classification tasks. The framework is adaptable to various graph structures.

This section reviews the landscape of research surrounding topology awareness in Graph Neural Networks (GNNs) and its connection to generalization performance. Despite the common belief that increasing topology awareness is beneficial, the precise impacts remain unclear. It also discusses the challenges of applying active learning to GNNs, particularly the cold-start problem, and proposes a novel approach that leverages graph structure over initial feature quality.

This paper introduces a framework to analyze the relationship between topology awareness and generalization performance in Graph Neural Networks (GNNs). It reveals that increased topology awareness can lead to uneven generalization across structural subgroups, challenging the assumption that enhancing topology awareness is always beneficial. A case study on shortest-path distance validates these findings and highlights practical applications in mitigating the cold start problem in...

Postman pre-request scripts streamline testing of APIs. The scripts automatically generate a random 12-character transaction reference. This random reference is shared with other endpoints, making it easy for the APIs to access the same reference seamlessly. The value generated gets reused across any endpoint that needs it, keeping my testing smooth and consistent.

Google Dorking is like using Google on steroids. It lets you dig deeper and discover things not easily visible to everyone. You can combine dorks in creative ways to gather more info about a target. Here are some useful Google dorks to level up your search skills.

Hyperhumans is a startup focused on AI solutions that enhance human capabilities, not replace them. Founded by tech enthusiasts, we create user-friendly AI tools that help both individuals and businesses streamline tasks and improve productivity. We emphasize privacy, flexibility, and ethical AI use.

The Ethereum blockchain is secure and decentralized but struggles with scalability, a key issue known as the Blockchain Trilemma. ZK-Rollups offer a solution by using Zero Knowledge Proofs (ZKPs) to validate transactions off-chain, enhancing scalability without compromising security or decentralization. While challenges like implementation complexity and data availability remain, ZK-Rollups are a promising technology to solve Ethereum's scalability issues and drive mass adoption.

$DOG of Bitcoin announces the release of its limited-edition $DOG Plushie on October 19, 2024. 100,000 individually serialized plushies will be available globally on launch day. Each plushie will wear one of three hoodie colors—Common, Uncommon, or Rare. The first 1,000 buyers will receive a complimentary Ordinals Profile Picture (PFP) NFT.

How are you, hacker? 🪐Want to know what's trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. Mapping CX/UX Research Competencies to Stay Human-Centered in Product Development By @pilyutikanna [ 9 Min read ] We create...

Silence is a word that is most often overlooked for its effects in any situation. It holds much power and can change the direction of conversations and self-improvement journeys. Rumi believed that silence is essential for connecting with one’s inner self and the divine presence.

In the eighth post of the #30DaysOfSwift series, let's make a Custom Tab Bar with animations and icons. Standard tab bars are fine, but a custom one adds that extra touch!

Data literacy is the ability to interpret and interact with information meaningfully. It includes critical thinking, problem-solving, communication, and visualization. To improve your data literacy, practice on any dataset available to you.

Aside from AlphaFold, Google Research, in part, is also working in quantum consciousness, with such an amateur theory that there is no hope it would ever answer the question. Google is also using computational science to map the brain, in connectomics, with zero to negligible theory, without even daring to check, observe, infer or question if the neuron is the basic unit of the...

There’s a new course on GraphAcademy: __[Building Knowledge Graphs with LLMs] Knowledge graphs are an essential tool in grounding GenAI applications. In this new course, you will learn how to create and query knowledge graphs using large language models (LLMs)

How are you, hacker? 🪐Want to know what's trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. How Fortnite Creative and UEFN Is The Next Big Creative Moneymaker and Why By @goldiechan [ 6 Min read ] Fortnite Creative ...

TL;DR: -Volante Chain aims to solve financial exclusion for 1.4 billion unbanked people worldwide -They offer Earned Wage Access (EWA), allowing employees to withdraw earned wages anytime -Uses blockchain for secure transactions and AI for risk assessment and financial modeling -Provides alternatives to traditional banking, including stable coin payments and fair international transfers -Faces challenges in regulatory compliance and integration with existing financial systems...

The article discusses the evolution of Ethereum Layer 2 solutions, starting with early attempts like State Channels and Plasma Chains, which aimed to reduce transaction execution time and congestion. It then explores the rise of Rollups, including Optimistic and Zero-Knowledge Rollups, which process transactions off-chain and enhance scalability while maintaining security. Finally, it introduces zkEVM, a new advancement that combines zero-knowledge proofs with Ethereum's...

Mixtral 8x7B introduces the first mixture-of-experts network to achieve state-of-the-art performance among open-source models, outperforming notable competitors like Claude-2.1 and GPT-3.5 Turbo. By utilizing only 13B active parameters per token, Mixtral maintains high efficiency while delivering superior results. The model will be shared under the Apache 2.0 license to foster advancements in AI applications across diverse fields.

The routing analysis of Mixtral shows no clear expert specialization across different domains, such as mathematics and biology, despite some differences observed in mathematics due to the dataset's synthetic nature. However, structured syntactic behavior is evident, with positional locality affecting expert assignments. This locality may impact model optimization for training and inference, suggesting potential strategies for caching and load balancing.

Mixtral – Instruct is fine-tuned through supervised methods and Direct Preference Optimization, earning a top score of 8.30 on MT-Bench. Independent evaluations confirm its superiority over major competitors, including GPT-3.5 Turbo and Llama 2 70B, making it the leading open-weights model as of December 2023.

Mixtral 8x7B outperforms Llama 2 70B in multilingual benchmarks for French, German, Spanish, and Italian due to enhanced multilingual training. It achieves 100% retrieval accuracy in long-range tasks and exhibits lower bias in sentiment analysis compared to Llama 2 on the BBQ and BOLD benchmarks, indicating its robustness and improved sentiment profile across diverse social categories.

Mixtral 8x7B surpasses Llama 2 70B and GPT-3.5 in numerous benchmarks, including commonsense reasoning, math, and code generation. With only 13B active parameters, Mixtral achieves comparable or superior performance while being more efficient than its counterparts. Despite its smaller capacity of 47B parameters, Mixtral excels in metrics like MMLU and demonstrates strong performance across a range of tasks, making it a robust choice for...

Mixtral utilizes a transformer architecture enhanced with Sparse Mixture of Experts (MoE) layers, allowing a dense context length of 32k tokens. The MoE layer's output is derived from the weighted sum of expert networks, enabling efficient processing on single GPUs and distribution across multiple GPUs using Expert Parallelism. While inspired by GShard, Mixtral's approach replaces all feedforward sub-blocks with MoE layers, optimizing performance and...

Mixtral is a sparse mixture of experts model (SMoE) with open weights, licensed under Apache 2.0. Mixtral outperforms Llama 2 70B and GPT-3.5 on most benchmarks. It is a decoder-only model where the feedforward block picks from 8 distinct groups of parameters.