MACHINE LEARNING

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Best Machine Learning Engineering Books Guide

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@gp_pulipaka

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11 January 2026 18h26

Best Books on Machine Learning Engineering! #BigData #Analytics #DataScience #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode https://
geni.us/ML-Best-Books

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Databricks Learning Festival: Master Data Engineering and AI

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@databricks

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11 January 2026 16h19

The Databricks Learning Festival is back!

Complete a self-paced learning pathway in data engineering, analytics, machine learning, generative AI, Apache Spark™, data warehousing, and more.

Finish all modules in at least one pathway to unlock:
– 50% off a Databricks… pic.twitter.com/LfSDeF5Psg
— Databricks (@databricks) 11 janvier 2026

The Databricks Learning Festival is back! Complete a self-paced learning pathway in data engineering, analytics, machine learning, generative AI, Apache Spark™, data warehousing, and more. Finish all modules in at least one pathway to unlock:
– 50% off a Databricks

Deep Delta Learning: Novel Residual Connection Operator

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11 January 2026 16h00

10. Deep Delta Learning Deep Delta Learning introduces a novel “Delta Operator” that generalizes residual connections by modulating the identity shortcut with a learnable, data-dependent geometric transformation.

SWE-EVO Benchmark for Long-Horizon Software Evolution Tasks

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11 January 2026 16h00

9. SWE-EVO SWE-EVO introduces a benchmark for evaluating coding agents on long-horizon software evolution tasks that require multi-step modifications spanning an average of 21 files per task.

Nemotron-Cascade: Cascaded Reinforcement Learning for Reasoning Models

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11 January 2026 16h00

4. Nemotron-Cascade Nemotron-Cascade introduces cascaded domain-wise reinforcement learning (Cascade RL) to build general-purpose reasoning models capable of operating in both instruct and deep thinking modes.

LLMs Evolve Competing Programs in Digital Red Queen Algorithm

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11 January 2026 16h00

3. Adversarial Program Evolution with LLMs

Digital Red Queen (DRQ) introduces an algorithm where LLMs evolve assembly-like programs called “warriors” that compete for control of a virtual machine in the game of Core War.https://t.co/u2OBC5HFxV
— DAIR.AI (@dair_ai) 11 janvier 2026

3. Adversarial Program Evolution with LLMs Digital Red Queen (DRQ) introduces an algorithm where LLMs evolve assembly-like programs called “warriors” that compete for control of a virtual machine in the game of Core War.

Scaling Compute Limits: Sara Hooker Challenges AI Growth Assumptions

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11 January 2026 16h00

1. On the Slow Death of Scaling This essay by Sara Hooker challenges the decade-long assumption that scaling compute always leads to better AI performance.

Top AI Research Papers: Agents, LLMs, and Scaling Evolution

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11 January 2026 16h00

The Top AI Papers of the Week (January 5-11) – GDPO
– SWE-EVO
– Deep Delta Learning
– Confucius Code Agent
– Recursive Language Models
– On the Slow Death of Scaling
– Adversarial Program Evolution with LLMs Read on for more:

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LoPA: 3x Faster AI Inference Without Additional Training

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@jiqizhixin

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11 January 2026 15h34

You could make AI inference 3x faster without any extra training. Researchers from SJTU & Huawei present LoPA just for that! Their new "Lookahead Parallel Decoding" method is a plug-and-play trick. It smartly predicts the best order to generate multiple tokens at once, instead