Sun.Jan 21, 2024

article thumbnail

Quiz of the Day (Excel) #15

Analytics Vidhya

Welcome to the AI Quiz on Excel! In this exciting exploration of artificial intelligence (AI) in spreadsheet software, we will explore the fascinating intersection of technology and data manipulation. As Excel continues to evolve, integrating AI features has become a game-changer, revolutionizing how we analyze, visualize, and interpret information.

article thumbnail

Google DeepMind Introduces AlphaGeometry: An Olympiad-Level Artificial Intelligence System for Geometry

Marktechpost

In a recent study, a team of researchers from Google DeepMind has introduced AlphaGeometry, an Artificial Intelligence (AI) system that can easily solve geometry Olympiad questions almost as well as a human gold medallist. Olympiad-level mathematical theorem proofs are noteworthy accomplishments that represent sophisticated automated reasoning abilities, especially in the difficult field of pre-university mathematics.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Enhancing Python Code: The Power of Effective Comments

Analytics Vidhya

Introduction When it comes to writing code in Python, it’s not just about creating functional and efficient programs. It’s also about making your code readable, maintainable, and collaborative. One way to achieve this is by writing comments in your Python code. Comments are lines of text that the Python interpreter ignores but provide valuable information […] The post Enhancing Python Code: The Power of Effective Comments appeared first on Analytics Vidhya.

Python 299
article thumbnail

This AI Paper from China Introduces a Groundbreaking Approach to Enhance Information Retrieval with Large Language Models Using the INTERS Dataset

Marktechpost

Large Language Models (LLMs) have exhibited remarkable prowess across various natural language processing tasks. However, applying them to Information Retrieval (IR) tasks remains a challenge due to the scarcity of IR-specific concepts in natural language. Addressing this, the idea of instruction tuning has emerged as a pivotal method to elevate LLMs’ capabilities and control.

article thumbnail

Usage-Based Monetization Musts: A Roadmap for Sustainable Revenue Growth

Speaker: David Warren and Kevin O'Neill Stoll

Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng

article thumbnail

Top 30 Deep Learning Interview Questions for Data Scientists

Analytics Vidhya

Introduction In the rapidly evolving field of data science, the demand for skilled professionals well-versed in deep learning is at an all-time high. As organizations understand the power of artificial intelligence to derive insights from vast datasets, data scientists equipped with deep learning expertise have become invaluable assets. Whether you are a seasoned data scientist […] The post Top 30 Deep Learning Interview Questions for Data Scientists appeared first on Analytics Vidhya.

More Trending

article thumbnail

Indentation in Python with Examples

Analytics Vidhya

Introduction Indentation plays a crucial role in Python programming. It is a unique feature of the language that sets it apart from other programming languages. In Python, indentation is used to define the structure and hierarchy of the code. It helps in visually organizing the code and making it more readable. This article will explore […] The post Indentation in Python with Examples appeared first on Analytics Vidhya.

Python 290
article thumbnail

This AI Paper from Johns Hopkins and Microsoft Revolutionizes Machine Translation with ALMA-R: A Smaller Sized LLM Model Outperforming GPT-4

Marktechpost

Machine translation, a crucial aspect of Natural Language Processing, has significantly increased. Yet, a primary challenge persists: producing translations beyond mere adequacy to reach near perfection. Traditional methods, while effective, often need to be improved by their reliance on large datasets and supervised fine-tuning (SFT), leading to limitations in the quality of the output.

LLM 137
article thumbnail

How to Convert Python Dictionary to Pandas DataFrame ?

Analytics Vidhya

Introduction Python is a versatile programming language that offers a wide range of data structures to work with. Two popular data structures in Python are dictionaries and pandas DataFrames. In this article, we will explore the process of converting a Python dictionary into a pandas DataFrame. Learn Introduction to Python Programming. Click here. What is a […] The post How to Convert Python Dictionary to Pandas DataFrame ?

Python 281
article thumbnail

UCLA Researchers Introduce Group Preference Optimization (GPO): A Machine Learning-based Alignment Framework that Steers Language Models to Preferences of Individual Groups in a Few-Shot Manner

Marktechpost

Large Language Models (LLMs) are increasingly employed for various domains, with use cases including creative writing, chatbots, and semantic search. Many of these applications are inherently subjective and require generations catering to different demographics, cultural and societal norms, or individual preferences. Through their large-scale training, current language models are exposed to diverse data that allows them to represent many such opinions.

article thumbnail

Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

article thumbnail

Image Resizing using OpenCV in Python

Analytics Vidhya

Introduction Image resizing is a crucial task in computer vision that involves changing the dimensions of an image while maintaining its aspect ratio. It is fundamental in various applications, including web development, computer vision tasks, and machine learning models. In this article, we will explore different image-resizing techniques using OpenCV, a popular library for computer […] The post Image Resizing using OpenCV in Python appeared first on Analytics Vidhya.

Python 277
article thumbnail

Decoding the Impact of Feedback Protocols on Large Language Model Alignment: Insights from Ratings vs. Rankings

Marktechpost

Alignment has become a pivotal concern for the development of next-generation text-based assistants, particularly in ensuring that large language models (LLMs) align with human values. This alignment aims to enhance LLM-generated content’s accuracy, coherence, and harmlessness in response to user queries. The alignment process comprises three key elements: feedback acquisition, alignment algorithms, and model evaluation.

article thumbnail

What is Ridge Regression? [Updated]

Great Learning

Contributed by: Prashanth Ashok Ridge regression is a model-tuning method that is used to analyze any data that suffers from multicollinearity. This method performs L2 regularization. When the issue of multicollinearity occurs, least-squares are unbiased, and variances are large, this results in predicted values being far away from the actual values.

article thumbnail

ByteDance AI Research Unveils Reinforced Fine-Tuning (ReFT) Method to Enhance the Generalizability of Learning LLMs for Reasoning with Math Problem Solving as an Example

Marktechpost

One effective method to improve the reasoning skills of LLMs is to employ supervised fine-tuning (SFT) with chain-of-thought (CoT) annotations. However, this approach has limitations in terms of generalization because it heavily depends on the provided CoT data. In scenarios like math problem-solving, each question in the training data typically has only one annotated reasoning path.

article thumbnail

15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

article thumbnail

Bin Prediction for Better Conformal Prediction

Machine Learning Research at Apple

This paper was accepted at the workshop on Regulatable ML at NeurIPS 2023. Conformal Prediction (CP) is a method of estimating risk or uncertainty when using Machine Learning to help abide by common Risk Management regulations often seen in fields like healthcare and finance. CP for regression can be challenging, especially when the output distribution is heteroscedastic, multimodal, or skewed.

article thumbnail

The Model Solving Geometry Problems at the Level of a Math Olympiad Gold Medalist

TheSequence

Created Using DALL-E Next Week in The Sequence: Edge 365: Our series about LLM reasoning continues with the famous ReAct technique including a review of the original paper by Google Research. We also explore Helicone to monitor LLMs. Edge 366: Reviews COSP and USP: Google Research New Methods to Advance Reasoning in LLMs You can subscribe below! TheSequence is a reader-supported publication.

LLM 59
article thumbnail

One Wide Feedforward is All You Need

Machine Learning Research at Apple

This paper was accepted at WMT conference at EMNLP. The Transformer architecture has two main non-embedding components: Attention and the Feed Forward Network (FFN). Attention captures interdependencies between words regardless of their position, while the FFN non-linearly transforms each input token independently. In this work, we explore the role of FFN and find that despite, and find that despite taking up a significant fraction of the model's parameters, it is highly redundant.

64
article thumbnail

Mastering ChatGPT: The Top 5 Free Courses

Robot Writers AI

CMSWire has come out with an extremely handy rundown of the top five free courses for mastering ChatGPT. Each course focuses on how to ‘prompt’ ChatGPT — or how to put together a string of words into ChatGPT– so you’re sure to get the exact writing or output you’re looking for. According to writer Scott Clark, the “comprehensive courses are available for those seeking a more in-depth understanding of what some are describing as both a science and an art

ChatGPT 52
article thumbnail

The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

article thumbnail

Hybrid Model Learning for Cardiovascular Biomarkers Inference

Machine Learning Research at Apple

This paper was accepted at the workshop Deep Generative Models for Health at NeurIPS 2023. Cardiovascular diseases (CVDs) are a major global health concern, making the longitudinal monitoring of cardiovascular biomarkers vital for early diagnosis and intervention. A core challenge is the inference of cardiac pulse parameters from pulse waves, especially when acquired from wearable sensors at peripheral body locations.

article thumbnail

Enhancing NLQ: Streamlined Integration of LLMs and Databases with LangChain

Mlearning.ai

Unlocking New Possibilities: Seamless LLM-Database Fusion with LangChain Continue reading on MLearning.

LLM 52
article thumbnail

Unbalanced Low-Rank Optimal Transport Solvers

Machine Learning Research at Apple

Two salient limitations have long hindered the relevance of optimal transport methods to machine learning. First, the computational cost of standard sample-based solvers (when used on batches of samples) is prohibitive. Second, the mass conservation constraint makes OT solvers too rigid in practice: because they must match textit{all} points from both measures, their output can be heavily influenced by outliers.

article thumbnail

Prompt Formatting is the Unsung Hero

Mlearning.ai

Your free and user friendly Blueprint to unlock the power of any AI Continue reading on MLearning.

article thumbnail

From Diagnosis to Delivery: How AI is Revolutionizing the Patient Experience

Speaker: Simran Kaur, Founder & CEO at Tattva Health Inc.

The healthcare landscape is being revolutionized by AI and cutting-edge digital technologies, reshaping how patients receive care and interact with providers. In this webinar led by Simran Kaur, we will explore how AI-driven solutions are enhancing patient communication, improving care quality, and empowering preventive and predictive medicine. You'll also learn how AI is streamlining healthcare processes, helping providers offer more efficient, personalized care and enabling faster, data-driven

article thumbnail

Simulation-based Inference for Cardiovascular Models

Machine Learning Research at Apple

This paper was accepted at the workshop Machine Learning and the Physical Sciences at NeurIPS 2023. Over the past decades, hemodynamics simulators have steadily evolved and have become tools of choice for studying cardiovascular systems in-silico. This comes naturally at the cost of increasing complexity since state-of-the-art models are non-linear partial differential equations depending on many parameters.

article thumbnail

Microsoft Presidio v2.2.352

Explosion

Context aware, pluggable and customizable PII de-identification and anonymization service for text and images, featuring a spaCy back-end.

article thumbnail

FastSR-NeRF: Improving NeRF Efficiency on Consumer Devices with A Simple Super-Resolution Pipeline

Machine Learning Research at Apple

Super-resolution (SR) techniques have recently been proposed to upscale the outputs of neural radiance fields (NeRF) and generate high-quality images with enhanced inference speeds. However, existing NeRF+SR methods increase training overhead by using extra input features, loss functions, and/or expensive training procedures such as knowledge distillation.

40