Artificial Intelligence In The Financial Industry
#AI #AIio #BigData #ML #NLU #Futureofwork @briansolis @Xbond49 @VitalikButerin @DataScienceCtrl @Benioff @johnnosta @IrmaRaste @Tiffani_Bova http://
ow.ly/YIG330sInw2
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Artificial Intelligence Applications and Impact on Financial Industry
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Alteryx workshop transforms data analytics workflows
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Curious how Alteryx can simplify data analytics? Join The Information Lab's beginner workshop on Dec 11 for live demos, hands-on exercises, & tips to transform workflows and uncover insights. Get started in a #DataDriven world! Register now: https://
ow.ly/N13s50UjiUZ -
Enterprise Machine Learning: Complete MLOps Platform Capabilities
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Enterprise #MachineLearning requires:
1. Data sources
2. Data pipelines
3. Feature stores
4. Model training
5. Model evaluation
6. Model deployment
7. Model monitoring
8. Predictions API
9. #MLOps Guess what?
The @AbacusAI platform provides all this capability for you! -
Human Oversight Critical for Preventing AI Model Behavior Reproduction
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@jefrankle
, Chief AI Scientist at Databricks, on the role of human oversight in #AI progress. "If you don't have human insight or a process for selecting relevant synthetic data, the model just reproduces its own behavior." -
Synthetic Data: Breaking Through AI Scaling Walls?
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is synthetic data the key to pushing past scaling walls or is the snake devoring its own tail?@poolsideai co-founder and cto @eisokant, explains why he’s an optimist in our recent discussion on @airstreetpress. pic.twitter.com/J5vtthzqF3
— Nathan Benaich (@nathanbenaich) 4 décembre 2024is synthetic data the key to pushing past scaling walls or is the snake devoring its own tail? @poolsideai co-founder and cto @eisokant
, explains why he’s an optimist in our recent discussion on @airstreetpress
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Improving Data Discovery in RAG Applications: From Keywords to GraphRAG
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Good morning everyone! In this iteration, we’re exploring how to improve how you find information in your RAG applications. We’ll cover everything from old-school keyword searches to more recent methods such as GraphRAG. By the end, you’ll know exactly how to make your data
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AI Use Cases in Industrial IoT Applications
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Use Cases for AI in IIoT >> https://
buff.ly/48TWrmX #sponsored #influxdata_iiot #InfluxDB #AI #IIoT @terence_mills @aicas_IoTvia @fogoros -
Computationally Efficient Methods for Robust Mean Estimation
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I wrote a survey article on computationally efficient methods for "robust" mean estimation, which includes robustness to contamination, heavy-tailed data, or in the sense of differential privacy. The same ideas are useful for all 3 (seemingly-different) forms of robustness! 1/2
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Manufacturing Leaders Use Automated Analytics to Cut Costs
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Spreadsheets can't keep up! See how manufacturing leaders use automated analytics to cut costs, boost efficiency, and drive revenue. Learn more: https://
ow.ly/HQsF50Ujivt #DataDrivenResults -
500 Case Studies in ML and LLM System Design
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Evidently AI – ML and LLM system design: 500 case studies https://
bit.ly/3Y7A1Lw
#AI #MachineLearning #DeepLearning #LLMs #DataScience