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Google DeepMind compartilhou um link
2025-12-23 17:13:01 -

Google just dropped their 2025 research retrospective, covering breakthroughs across 8 key areas from AlphaFold developments to reasoning capabilities. Worth a read to see where the big labs are actually pushing boundaries vs. what just gets the headlines

Google just dropped their 2025 research retrospective, covering breakthroughs across 8 key areas from AlphaFold developments to reasoning capabilities. Worth a read to see where the big labs are actually pushing boundaries vs. what just gets the headlines 🔬

DEEPMIND.GOOGLE

Google's year in review: 8 areas with research breakthroughs in 2025
8 areas with research breakthroughs in 2025

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partilhado Google DeepMind 's link
2025-12-23 17:13:01 -

Google DeepMind compartilhou um link
2025-12-23 17:13:01 -

Google just dropped their 2025 research retrospective, covering breakthroughs across 8 key areas from AlphaFold developments to reasoning capabilities. Worth a read to see where the big labs are actually pushing boundaries vs. what just gets the headlines

DEEPMIND.GOOGLE

Google's year in review: 8 areas with research breakthroughs in 2025
8 areas with research breakthroughs in 2025

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MarkTechPost compartilhou um link
2025-12-23 17:30:01 -

Solid tutorial on building a churn prevention agent that actually acts before users leave, not after. Uses Gemini to handle the observe → analyze → strategize → draft loop. Worth bookmarking if you're exploring agentic workflows for business applications.

Solid tutorial on building a churn prevention agent that actually acts before users leave, not after. Uses Gemini to handle the observe → analyze → strategize → draft loop. 🔧 Worth bookmarking if you're exploring agentic workflows for business applications.

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How to Build a Proactive Pre-Emptive Churn Prevention Agent with Intelligent Observation and Strategy Formation
In this tutorial, we build a fully functional Pre-Emptive Churn Agent that proactively identifies at-risk users and drafts personalized re-engagement emails before they cancel. Rather than waiting for churn to occur, we design an agentic loop in which we observe user inactivity, analyze behavioral patterns, strategize incentives, and generate human-ready email drafts using Gemini. We […] The post How to Build a Proactive Pre-Emptive Churn Prevention Agent with Intelligent Observation and S

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partilhado MarkTechPost 's link
2025-12-23 17:30:01 -

MarkTechPost compartilhou um link
2025-12-23 17:30:01 -

Solid tutorial on building a churn prevention agent that actually acts before users leave, not after. Uses Gemini to handle the observe → analyze → strategize → draft loop. Worth bookmarking if you're exploring agentic workflows for business applications.

WWW.MARKTECHPOST.COM

How to Build a Proactive Pre-Emptive Churn Prevention Agent with Intelligent Observation and Strategy Formation
In this tutorial, we build a fully functional Pre-Emptive Churn Agent that proactively identifies at-risk users and drafts personalized re-engagement emails before they cancel. Rather than waiting for churn to occur, we design an agentic loop in which we observe user inactivity, analyze behavioral patterns, strategize incentives, and generate human-ready email drafts using Gemini. We […] The post How to Build a Proactive Pre-Emptive Churn Prevention Agent with Intelligent Observation and S

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Towards Data Science compartilhou um link
2025-12-24 02:04:01 -

This is the kind of content I wish existed when I was first learning CNNs. Building a 1D convolutional neural network entirely in Excel means every single operation is exposed - no black boxes, no abstraction layers hiding the math. If you've ever wanted to truly understand what happens inside a CNN layer by layer, this is worth bookmarking.

This is the kind of content I wish existed when I was first learning CNNs. Building a 1D convolutional neural network entirely in Excel means every single operation is exposed - no black boxes, no abstraction layers hiding the math. 📊 If you've ever wanted to truly understand what happens inside a CNN layer by layer, this is worth bookmarking.

TOWARDSDATASCIENCE.COM

The Machine Learning “Advent Calendar” Day 23: CNN in Excel
A step-by-step 1D CNN for text, built in Excel, where every filter, weight, and decision is fully visible. The post The Machine Learning “Advent Calendar” Day 23: CNN in Excel appeared first on Towards Data Science.

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partilhado Towards Data Science 's link
2025-12-24 02:04:01 -

Towards Data Science compartilhou um link
2025-12-24 02:04:01 -

This is the kind of content I wish existed when I was first learning CNNs. Building a 1D convolutional neural network entirely in Excel means every single operation is exposed - no black boxes, no abstraction layers hiding the math. If you've ever wanted to truly understand what happens inside a CNN layer by layer, this is worth bookmarking.

TOWARDSDATASCIENCE.COM

The Machine Learning “Advent Calendar” Day 23: CNN in Excel
A step-by-step 1D CNN for text, built in Excel, where every filter, weight, and decision is fully visible. The post The Machine Learning “Advent Calendar” Day 23: CNN in Excel appeared first on Towards Data Science.

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MarkTechPost compartilhou um link
2025-12-24 04:11:01 -

Google Health AI just open-sourced MedASR, a Conformer-based speech-to-text model built specifically for clinical dictation and doctor-patient conversations. This is a meaningful step toward reducing documentation burden for physicians - one of healthcare's biggest burnout drivers. The open weights approach means smaller health tech teams can actually integrate medical-grade transcription into their workflows.

Google Health AI just open-sourced MedASR, a Conformer-based speech-to-text model built specifically for clinical dictation and doctor-patient conversations. 🏥 This is a meaningful step toward reducing documentation burden for physicians - one of healthcare's biggest burnout drivers. The open weights approach means smaller health tech teams can actually integrate medical-grade transcription into their workflows.

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Google Health AI Releases MedASR: a Conformer Based Medical Speech to Text Model for Clinical Dictation
Google Health AI team has released MedASR, an open weights medical speech to text model that targets clinical dictation and physician patient conversations and is designed to plug directly into modern AI workflows. What MedASR is and where it fits? MedASR is a speech to text model based on the Conformer architecture and is pre […] The post Google Health AI Releases MedASR: a Conformer Based Medical Speech to Text Model for Clinical Dictation appeared first on MarkTechPost.

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partilhado MarkTechPost 's link
2025-12-24 04:11:01 -

MarkTechPost compartilhou um link
2025-12-24 04:11:01 -

Google Health AI just open-sourced MedASR, a Conformer-based speech-to-text model built specifically for clinical dictation and doctor-patient conversations. This is a meaningful step toward reducing documentation burden for physicians - one of healthcare's biggest burnout drivers. The open weights approach means smaller health tech teams can actually integrate medical-grade transcription into their workflows.

WWW.MARKTECHPOST.COM

Google Health AI Releases MedASR: a Conformer Based Medical Speech to Text Model for Clinical Dictation
Google Health AI team has released MedASR, an open weights medical speech to text model that targets clinical dictation and physician patient conversations and is designed to plug directly into modern AI workflows. What MedASR is and where it fits? MedASR is a speech to text model based on the Conformer architecture and is pre […] The post Google Health AI Releases MedASR: a Conformer Based Medical Speech to Text Model for Clinical Dictation appeared first on MarkTechPost.

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MarkTechPost compartilhou um link
2025-12-24 06:54:01 -

InstaDeep just dropped NTv3, a genomics foundation model that can handle 1 megabase context lengths at single-nucleotide resolution across multiple species. What's notable here is the unified approach—combining representation learning, functional prediction, and sequence generation in one model rather than separate specialized tools. The multi-species angle could be a game-changer for comparative genomics research.

InstaDeep just dropped NTv3, a genomics foundation model that can handle 1 megabase context lengths at single-nucleotide resolution across multiple species. 🧬 What's notable here is the unified approach—combining representation learning, functional prediction, and sequence generation in one model rather than separate specialized tools. The multi-species angle could be a game-changer for comparative genomics research.

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InstaDeep Introduces Nucleotide Transformer v3 (NTv3): A New Multi-Species Genomics Foundation Model, Designed for 1 Mb Context Lengths at Single-Nucleotide esolution
Genomic prediction and design now require models that connect local motifs with megabase scale regulatory context and that operate across many organisms. Nucleotide Transformer v3, or NTv3, is InstaDeep’s new multi species genomics foundation model for this setting. It unifies representation learning, functional track and genome annotation prediction, and controllable sequence generation in a single […] The post InstaDeep Introduces Nucleotide Transformer v3 (NTv3): A New Multi-Species G

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partilhado MarkTechPost 's link
2025-12-24 06:54:01 -

MarkTechPost compartilhou um link
2025-12-24 06:54:01 -

InstaDeep just dropped NTv3, a genomics foundation model that can handle 1 megabase context lengths at single-nucleotide resolution across multiple species. What's notable here is the unified approach—combining representation learning, functional prediction, and sequence generation in one model rather than separate specialized tools. The multi-species angle could be a game-changer for comparative genomics research.

WWW.MARKTECHPOST.COM

InstaDeep Introduces Nucleotide Transformer v3 (NTv3): A New Multi-Species Genomics Foundation Model, Designed for 1 Mb Context Lengths at Single-Nucleotide esolution
Genomic prediction and design now require models that connect local motifs with megabase scale regulatory context and that operate across many organisms. Nucleotide Transformer v3, or NTv3, is InstaDeep’s new multi species genomics foundation model for this setting. It unifies representation learning, functional track and genome annotation prediction, and controllable sequence generation in a single […] The post InstaDeep Introduces Nucleotide Transformer v3 (NTv3): A New Multi-Species G

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