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Whitepapers

September 26, 2025

Audio Data for AI Models: End-to-End ɫ�� from Collection to Deployment

End-to-end audio data for voice AI. Collect, transcribe, and validate speech across 500+ languages with ɫ��’s global network.

September 24, 2025

Red Teaming Multimodal Language Models: Evaluating Harm Across Prompt Modalities and Models

Discover where multilingual AI translation falls short and why human oversight is key to accurate localisation.

August 27, 2025

Retail AI: the Future of Shopping

Learn how retail AI will redefine tomorrow’s shopping experiences with practical insights for leaders in retail and e-commerce.

Multilingual LLM Translation: Evaluating Cultural Nuance in Generative AI

Discover where multilingual AI translation falls short and why human oversight is key to accurate localisation.

Adversarial Prompting: Benchmarking Safety in Large Language Models

Benchmarking adversarial prompting in LLMs: Discover how attackers bypass AI safeguards—and what it takes to build safer, more resilient models.

February 28, 2025

AI Safety: Building Responsible and Reliable System

Explore research-based strategies for AI safety, including risk mitigation and end user alignment.

December 3, 2024

Mastering Large Language Models: A Deep Dive for AI Leaders

Explore cutting-edge advancements, data optimization strategies, and ethical considerations to unlock AI's full potential for your enterprise.

October 22, 2024

2024 State of AI Report: Navigate the Evolving AI Landscape

Explore the latest AI trends in ɫ��'s 2024 State of AI Report to make informed business decisions.

September 24, 2024

How RAG and Human Expertise Optimize AI Performance

Discover how combining Retrieval Augmented Generation (RAG) with human expertise drives high-quality AI results.

Guide to Chain-of-Thought Prompting

How chain of thought prompting enhances LLM reasoning - featuring an expert case study on mathematical reasoning for a leading technology company.

January 25, 2023

THE STATE OF AI AND MACHINE LEARNING FOR AUTOMOTIVE 2023

The State of AI and Machine Learning for Automotive leverages data from our 8th annual State of AI and Machine Learning Report to explore the trends and perception of the future of AI for the automotive industry. With advancements in technology, we’re seeing the impacts of human-in-the-loop annotation, the implementation of new vehicle features, and innovations in driver autonomy contributing ...

September 12, 2022

ɫ��'s 2022 Annual State of AI and Machine Learning Report

The State of AI and Machine Learning is a cross-industry effort aimed at providing an overview of the status of artificial intelligence and machine learning through input from businesses and their senior decision-makers and technical. For our 8th annual edition, ɫ�� partnered with The Harris Poll to expand our survey to 504 participants in North America and Europe. The goal ...

September 8, 2022

AI ɫ�� for the Automotive Industry

Launching Customer-centric AI for Autonomous Vehicles and Smart Cars The auto industry is undergoing a profound transformation, with AI and electric changing the way companies build cars and influencing the type of consumer that will ultimately buy or use those cars. The future of transportation will be built with world-class AI, ultra-fast connectivity, and environmental impact in mind. The potential

The 2021 State of AI and Machine Learning Report

Since 2016, the State of AI and Machine Learning Report has given insight into the adoption, implementation and scale of AI across industries. This large-organization study of senior business leaders and technologists details where organizations are within their AI journey — from the types of data they leverage to the tools they use and budgets they have. This year’s report ...

The Ultimate Guide to AI Training Data Platforms

Everything you need to know to find the right training data platform to suit your machine learning needs  Effective machine learning projects begin and end with quality training data and finding the right platform to support your AI model needs is the first step on your path to success.  If you’re looking to launch an AI algorithm or machine learning ...

September 27, 2021

Data-Centric Computer Vision

Approaches, Applications, and Best Practices using the ɫ�� Data Annotation Platform Human vision systems have the advantage of learning from a lifetime of experiences how to contextualize the things we see. Machine learning models, on the other hand, usually need a substantial number of real-world scenarios to learn from to be able to product reliable computer vision (CV) outputs

January 28, 2021

Responsible AI from Pilot to Production

Artificial Intelligence (AI) has the potential to add $13 trillion to our global economy by 2030, according to McKinsey. Those who have successfully deployed AI see high returns on investment and increased customer satisfaction through more personalized, efficient AI tools. With AI investment growing and teams rushing to find ways to bring it into the core of their business

September 15, 2020

Driving ROI Through AI

In an effort to help executives working to drive ROI from AI, we worked together with ESI ThoughtLab and a group of other AI leaders – including Cognizant, Cortex, Dataiku, DataRobot, Deloitte, and Publicis Sapient – to produce this report based on a survey of 1,200 organizations. This benchmarking study spans across a wide section of industries and world markets ...

AI ɫ�� for Financial Services

Key Steps to Building Customer-Centric AI According to Cambridge Centre for Alternative Finance, by 2022, nearly 64% of financial service companies expect to be “mass adopters” of AI — using it for revenue generation, process automation, risk management, customer service, and client acquisition — compared with just 16% currently. Yet success isn’t guaranteed. In fact, industry analysts find that the

The Essential Guide to Training Data for AI and ML

Why Your AI Model is Only as Good as Its Training Data There’s a saying of garbage in, garbage out when it comes to artificial intelligence and machine learning. It’s common knowledge that every machine learning solution needs a good algorithm powering it, but what gets far less press is what actually goes into these algorithms: the training data itself

How to Create an AI Center of Excellence for Enterprise

Learn why creating an AI Center of Excellence will facilitate increased returns on AI investments. It will likely take time and cycles, tons of training data, algorithms, use cases, and several stakeholders involved in order to uncover its value. Yet it will be worth it as you build momentum for your team and business. Building an AI Center of Excellence

January 15, 2020

AIOps for Business Leaders

Over a petabyte of data gets consumed by many companies, but repurposing that high-quality training data for machine learning and artificial intelligence initiatives can be a heavy uplift. This high-quality training data is critical for moving AI and ML algorithms from experiment, all the way to core business. Business leaders are turning to AIOps and professional services to guide the

The 2020 State of AI and Machine Learning Report

The 2020 State of AI and Machine Learning report illustrates the current state of artificial intelligence and machine learning, showcasing where the industry is as a whole in 2020 compared to 2019. The 2020 report is the output of a cross-industry, large-organization study of senior business leaders and technologists. It details where organizations are within the AI journey and provides