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The market size in the AI market is projected to reach $184bn in 2024

AI News

According to today’s experts, by 2033, robots will be doing almost 40% of our housework. The experts predict that by 2033 almost 60% of our grocery shop will be performed by AI. What a user sees is personalised because the algorithm has learned what posts you react to based on your history. AI also updates social media feeds.

Robotics 292
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AI Infrastructure Anticipated to Hit $420 Billion By 2033

ODSC - Open Data Science

Another report by Precedence Research says that the global AI infrastructure market size, valued at USD 37B in 2023, is anticipated to reach around USD 421B by 2033, growing at a CAGR of 27.53% from 2024 to 2033.

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Four Growers Secures $9M Series A to Revolutionize Greenhouse Farming with AI and Robotics

Unite.AI

34x faster pathfinding than standard motion planning algorithms, ensuring optimal harvesting paths. through 2033, according to a study by Fact.MR. The GR-100 boasts: 5x faster picking speeds than competitors, harvesting up to 43 kilograms per hour of cherry and grape tomatoes. The indoor farming market, valued at $40.51

Robotics 162
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When AI Meets User Experience: Challenges Linger, Opportunities Shine Ever Brighter

Unite.AI

Bureau of Labor Statistics anticipates a 16% increase in employment from 2022 to 2033, significantly outpacing the average growth rate. Thanks to the potential of AI algorithms to process information of this magnitude, analyzing consumer sentiments (from social media platforms, forums, etc.)

UX Design 182
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Beyond the Human Eye: Enhancing Nondestructive Testing with AI Insights

Aiiot Talk

billion valuation by 2033. Using AI to Enhance Pattern Recognition Advanced AI algorithms trained on large enough datasets can find various patterns and provide detailed insights into the condition of materials. AI algorithms’ predictive analytic capabilities also help anticipate potential failures.

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Learn The Mathematics Behind Gradient Descent in Deep Learning

Pickl AI

billion by 2033, growing at a CAGR of 32.57%. The algorithm moves toward the steepest decline to find the minimum point. Types of Gradient Descent In Deep Learning and Machine Learning, gradient descent is the algorithm used to minimise the loss function by updating the model’s parameters. 32 or 64 examples).

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All Languages Are NOT Created (Tokenized) Equal

Topbots

I used the dev split of the dataset, which consists of 2033 texts translated into each of the languages. Distribution of token lengths for all 2033 messages and 52 languages. A comprehensive explanation of the BPE algorithm can be found on the HuggingFace Transformers course. Figure created by author.