November, 2022

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Building Our Applications Using Flutter

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Flutter where F stands for Front- end, L stands for Language, U stands for UI layout, T stands for Time, T stands for Tools, E stands for Enable, and R stands for Rich. In other words, Flutter is a tool used in […]. The post Building Our Applications Using Flutter appeared first on Analytics Vidhya.

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AI for product managers: Today’s top terms to stay in the know

AssemblyAI

Progress in AI is exploding – the AI industry’s value is projected to grow by over 13x over the next eight years. Now, product-led growth (PLG) companies are racing to take advantage of this high-value opportunity by embedding AI into key features that improve user experience, capture new markets, and drive adoption. Jasper, for example, is a PLG company that uses AI to generate automated marketing copy.

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Notes on an Experiment with Markets

AI Impacts

Jeffrey Heninger, 22 November 2022 AI Impacts is a research group with seven employees. From Oct 31 - Nov 3, we had a work retreat. We decided to try using Manifold Markets to help us plan social events in the evenings. Here are some notes from this experiment. Structure of the Experiment Katja created a group on Manifold Markets for AI Impacts, and an initial collection of markets.

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Why is MSE = Bias² + Variance?

Cassie Kozyrkov

Introduction to “good” statistical estimators and their properties Continue reading on Towards Data Science »

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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

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Text-to-Image: Diffusion, Text Conditioning, Guidance, Latent Space

Eugene Yan

The fundamentals of text-to-image generation, relevant papers, and experimenting with DDPM.

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How to Use DevOps Azure to Create CI and CD Pipelines?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction In this article, we will discuss DevOps, two phases of DevOps, its advantages, and why we need DevOps along with CI and CD Pipelines. Before DevOps, software development teams, quality assurance (QA) teams, security, and operations would test the code for several […].

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DeepMind's AlphaTensor Explained

AssemblyAI

At the bedrock of the Deep Learning that powers incredible technologies like text-to-image models lies matrix multiplication. Regardless of the specific architecture employed, (nearly) every Neural Network relies on efficient matrix multiplication to learn and infer. Finding efficient and fast matrix multiplication algorithms is therefore paramount given that they will supercharge every neural network, potentially allowing us to run models prohibited by our current hardware limitations.

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Against a General Factor of Doom

AI Impacts

Jeffrey Heninger, 22 November 2022 I was recently reading the results of a survey asking climate experts about their opinions on geoengineering. The results surprised me: “We find that respondents who expect severe global climate change damages and who have little confidence in current mitigation efforts are more opposed to geoengineering than respondents who are less pessimistic about global damages and mitigation efforts.”[note] Dannenberg & Zitzelsberger.

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Overusing the Term “Statistically Significant” Makes You Look Clueless

Cassie Kozyrkov

A primer on interpreting other people’s hypothesis tests Continue reading on Towards Data Science »

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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?

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The pursuit of AI education - past, present, and future

DeepMind

Meet Sylvia Christie, our education partnerships manager who’s played a leading role in expanding our scholarship programme, which is marking its five-year anniversary.

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Characterizing Emergent Phenomena in Large Language Models

Google Research AI blog

Posted by Jason Wei and Yi Tay, Research Scientists, Google Research, Brain Team The field of natural language processing (NLP) has been revolutionized by language models trained on large amounts of text data. Scaling up the size of language models often leads to improved performance and sample efficiency on a range of downstream NLP tasks. In many cases, the performance of a large language model can be predicted by extrapolating the performance trend of smaller models.

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Top 5 Interview Questions on Multi-modal Transformers

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: totaljobs.com Introduction Until recently, developing new, improved transformers specifically for a single modality was common practice. However, to tackle real-world tasks, there was a pressing need to develop multi-modal transformers models. Multi-modal transformers models are the type of models that employ the […].

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AI research review - Merging Models Modulo Permutation Symmetries

AssemblyAI

This week’s AI Research Review is Git Re-Basin: Merging Models Modulo Permutation Symmetries. Git Re-Basin: Merging Models Modulo Permutation Symmetries What’s Exciting About this Paper In this paper , the authors show that the loss landscape of a wide enough neural network has essentially a single basin. This leads to many permutations of the same model weights calculating the same function.

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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

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Stable Diffusion with Core ML on Apple Silicon

Machine Learning Research at Apple

Today, we are excited to release optimizations to Core ML for Stable Diffusion in macOS 13.1 and iOS 16.2, along with code to get started with deploying to Apple Silicon devices. Figure 1: Images generated with the prompts, "a high quality photo of an astronaut riding a (horse/dragon) in space" using Stable Diffusion and Core ML + diffusers running on-device on Apple Silicon.

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The Obscure Art of Data Design

Cassie Kozyrkov

Battling an embarrassing new alchemy for the digital era Continue reading on Towards Data Science »

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Building interactive agents in video game worlds

DeepMind

Most artificial intelligence (AI) researchers now believe that writing computer code which can capture the nuances of situated interactions is impossible. Alternatively, modern machine learning (ML) researchers have focused on learning about these types of interactions from data. To explore these learning-based approaches and quickly build agents that can make sense of human instructions and safely perform actions in open-ended conditions, we created a research framework within a video game envi

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ReAct: Synergizing Reasoning and Acting in Language Models

Google Research AI blog

Posted by Shunyu Yao, Student Researcher, and Yuan Cao, Research Scientist, Google Research, Brain Team Recent advances have expanded the applicability of language models (LM) to downstream tasks. On one hand, existing language models that are properly prompted, via chain-of-thought , demonstrate emergent capabilities that carry out self-conditioned reasoning traces to derive answers from questions, excelling at various arithmetic, commonsense, and symbolic reasoning tasks.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Comprehensive Guide for Interview Questions on Transfer Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: Canva Introduction Competitive Deep Learning models rely on a wealth of training data, computing resources, and time. However, there are many tasks for which we don’t have enough labeled data at our disposal. Moreover, the need for running deep learning models on […].

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ChatGPT: Optimizing Language Models for Dialogue

OpenAI

We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT , which is trained to follow an instruction in a prompt and provide a detailed response.

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Why is Git Not the Best for ML Model Version Control

The MLOps Blog

These days enterprises are sitting on a pool of data and increasingly employing machine learning and deep learning algorithms to forecast sales, predict customer churn and fraud detection, etc., across industries and domains. Data science practitioners experiment with algorithms, data, and hyperparameters to develop a model that generates business insights.

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Hiring Clinical Faculty for 2023: Interview with CDS Clinical Associate Professor Pascal Wallisch

NYU Center for Data Science

Pascal Wallisch, CDS Clinical Associate Professor We are currently hiring Clinical Faculty for 2023. The position has the opportunity to make a significant impact by teaching data science courses at the undergraduate and graduate levels. We caught up with CDS Clinical Associate Professor Pascal Wallisch to discuss his experience as a clinical faculty member at CDS as well as what the role has to offer incoming hires.

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The Tumultuous IT Landscape Is Making Hiring More Difficult

After a year of sporadic hiring and uncertain investment areas, tech leaders are scrambling to figure out what’s next. This whitepaper reveals how tech leaders are hiring and investing for the future. Download today to learn more!

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Best practices for data enrichment

DeepMind

At DeepMind, our goal is to make sure everything we do meets the highest standards of safety and ethics, in line with our Operating Principles. One of the most important places this starts with is how we collect our data. In the past 12 months, we’ve collaborated with Partnership on AI (PAI) to carefully consider these challenges, and have co-developed standardised best practices and processes for responsible human data collection.

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Making a Traversable Wormhole with a Quantum Computer

Google Research AI blog

Posted by Alexander Zlokapa, Student Researcher, and Hartmut Neven, VP of Engineering, Quantum AI Team Wormholes — wrinkles in the fabric of spacetime that connect two disparate locations — may seem like the stuff of science fiction. But whether or not they exist in reality, studying these hypothetical objects could be the key to making concrete the tantalizing link between information and matter that has bedeviled physicists for decades.

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Hierarchical Clustering in Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Hierarchical clustering is one of the most famous clustering techniques used in unsupervised machine learning. K-means and hierarchical clustering are the two most popular and effective clustering algorithms. The working mechanism they apply in the backend allows them to provide such a […].

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Languages You Know Influence Those You Learn: Impact of Language Characteristics on Multi-Lingual Text-to-Text Transfer

Machine Learning Research at Apple

Multi-lingual language models (LM), such as mBERT, XLM-R, mT5, mBART, have been remarkably successful in enabling natural language tasks in low-resource languages through cross-lingual transfer from high-resource ones. In this work, we try to better understand how such models, specifically mT5, transfer any linguistic and semantic knowledge across languages, even though no explicit cross-lingual signals are provided during pre-training.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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Google builds Expert Choice Routing on top of MOE

Bugra Akyildiz

Articles Google published an Expert Choice Routing advancement in the Mixture of Experts modeling architecture for their large scale model. In this scheme, they set expert capacity k as the average tokens per expert in a batch of input sequences multiplied by a capacity factor , which determines the average number of experts that can be received by each token.

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DirectX

NVIDIA Developer

DIRECTX 12 ULTIMATE DirectX 12 Ultimate 是 Microsoft 的最新图形 API,整合了 NVIDIA RTX 的创新技术,这些技术于 2018 年首次推出,是新一代实时图形的跨平台标准。它提供用于光线追踪、可变速率着色、网格着色、采样器反馈等的 API,让开发者能够将影院级反射、阴影和照明技术用于游戏和实时应用。借助 DirectX 12 Agility SDK ,开发者可在 2019 年 11 月及更新版本的 Windows 10 上立即获得新推出的光线追踪技术和图形 API。 光线追踪 实时光线追踪,可利用 NVIDIA RTX RT Core 实现逼真的反射、照明和阴影。 网格着色 将顶点和原始处理相结合的新型着色器,提高了几何管线的灵活性和性能。

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Mastering Stratego, the classic game of imperfect information

DeepMind

Game-playing artificial intelligence (AI) systems have advanced to a new frontier. Stratego, the classic board game that’s more complex than chess and Go, and craftier than poker, has now been mastered. Published in Science, we present DeepNash, an AI agent that learned the game from scratch to a human expert level by playing against itself.