AIMultiple

We benchmarked Mistral’s new OCR across 300 documents in handwriting, printed media and printed text. OCR 3 is behind Gemini and others. With a 6% difference in a dataset of 300 documents, the difference is statistically significant.

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It reminds me of Grok 4 which aced every good benchmark with a holdout dataset like LiveCodeBench. AI influencers were impressed. Then we tested it and got disappointed. In most cases, like the hallucination benchmark below, it failed to reach the top position.

ChatGPT's new agent almost broke our benchmark. We'll soon need a harder test. This benchmark is not based on a public dataset that is included in OpenAI's models. While we explain the task clearly, data is not public, therefore models not have access to it.

For details: research.aimultiple.com/ai-code/

This is a benchmark performed on the holdout set. We published 1 example question but the rest of the 100 questions are not public. Therefore, models can't just respond with the answers in their training set.

We are introducing AI LMC-Eval, a coding benchmark with 100 questions & tested on 7 leading LLMs. LMC stands for Logic / Math Coding. We presented the LLM with high school level logic and math problems and instructed it to write Python to solve them.

Agentic AI is still mostly hype. We asked 5 AI agents to fetch a prices of a specific product from original sources and got only 20% of the results. Should we try this with other agents? research.aimultiple.com/ai-agents/

#ArtificialIntelligence is a game-changing technology for businesses, but there are still many myths and unclear points about AI. Take a look at our article to learn about them. research.aimultiple.com/ai-stats/ #MachineLearning

@AIMultiple says most companies today allocate nearly 50% of their QA budgets to test automation! Why is automating QA so important? Learn about its impact for rapid product release cycle in our blog: hubs.la/Q01ygqCz0 #Calsoft #QA #QAAutomation #ProductEngineering

Digital transformation is integrating digital technologies into all aspects of a business to meet the market and changing business requirements. Learn about why digital transformation matters and some use cases: research.aimultiple.com/digital-transf… #digitaltransformation

Web scraping enables businesses to get a bulk list of their target audience’s email addresses. It reduces human errors in manually entering email addresses into a database and accelerates marketing processes. To learn more, read our comprehensive article. research.aimultiple.com/email-scraping/

Psychological factors such as users’ sentiments regarding policy changes or new investments greatly influence how stock prices change. In this article, we’ll explore how sentiment analysis can be applied to stock market forecasts. #StockMarkets research.aimultiple.com/sentiment-anal…

@sridharseshadri @dilmegani @SpirosMargaris @JoannMoretti @AkwyZ @DeepLearn007 @Nicochan33 @jblefevre60 Thank you for sharing!

The Ultimate Guide to Synthetic Data: Uses, Benefits & Tools research.aimultiple.com/synthetic-data/ @dilmegani via @aimultiple #DataScience #AI #MachineLearning Cc @SpirosMargaris @JoannMoretti @AkwyZ @DeepLearn007 @Nicochan33 @jblefevre60

IoT enables a myriad of different business applications. Knowing those IoT use cases can help businesses integrate IoT technologies into their investment decisions. That is why we created the most comprehensive list of IoT use cases in industries. #IoT research.aimultiple.com/iot-applicatio…

AI presents opportunities for cybersecurity professionals to improve their cyber defenses and new threats as cyber attackers leverage modern, publicly available machine learning algorithms. Check our comprehensive article on AI security. #cyberattack research.aimultiple.com/ai-security/

Why using edge computing for IoT devices can be a better alternative than the cloud? Here are some examples of IoT devices using edge computing for storage and data processing. research.aimultiple.com/iot-edge/ #edgecomputing

Annotated data is integral to many machine learning and artificial intelligence applications. At the same time, it is one of the most time-consuming and labor-intensive parts of ML projects. Here, we explore what data annotation is and why it matters. research.aimultiple.com/data-annotatio…

@itsmuzza2004 @ipfconline1 @dilmegani @SpirosMargaris @JoannMoretti @AkwyZ @DeepLearn007 @Nicochan33 @jblefevre60 Thanks for sharing! 🙏

RT @ipfconline1: The Ultimate Guide to Synthetic Data: Uses, Benefits & Tools research.aimultiple.com/synthetic-data/ @dilmegani via @aimultiple #DataScience #AI #MachineLearning Cc @SpirosMargaris @JoannMoretti @AkwyZ @DeepLearn007 @Nicochan33 @jblefevre60