Articles for author: ikayaniaamirshahzad@gmail.com

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link

Dubformer Raises $3.6M to Revolutionize AI Dubbing with Emotion Transfer Technology

AI dubbing startup Dubformer has secured a $3.6 million seed funding round to redefine how emotional depth is captured in media localization. The investment, led by Almaz Capital with participation from s16vc and FinSight, as well as angel investors including Arul Menezes, founder of Microsoft Translator, and Funa Maduka, former head of International Original Film at Netflix, will fuel the company’s mission to make dubbed content more immersive and engaging for audiences worldwide. Solving AI Dubbing’s Biggest Challenge Despite significant advancements in AI dubbing, most solutions still struggle to convey authentic emotion in voiceovers. Research shows that audiences can easily distinguish

Title Launch Observability at Netflix Scale | by Netflix Technology Blog | Mar, 2025

Part 3: System Strategies and Architecture By: Varun Khaitan With special thanks to my stunning colleagues: Mallika Rao, Esmir Mesic, Hugo Marques This blog post is a continuation of Part 2, where we cleared the ambiguity around title launch observability at Netflix. In this installment, we will explore the strategies, tools, and methodologies that were employed to achieve comprehensive title observability at scale. To create a comprehensive solution, we decided to introduce observability endpoints first. Each microservice involved in our Personalization stack that integrated with our observability solution had to introduce a new “Title Health” endpoint. Our goal was for

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link

“Wooly mice” a test run for mammoth gene editing

On Tuesday, the team behind the plan to bring mammoth-like animals back to the tundra announced the creation of what it is calling wooly mice, which have long fur reminiscent of the woolly mammoth. The long fur was created through the simultaneous editing of as many as seven genes, all with a known connection to hair growth, color, and/or texture. But don’t think that this is a sort of mouse-mammoth hybrid. Most of the genetic changes were first identified in mice, not mammoths. So, the focus is on the fact that the team could do simultaneous editing of multiple genes—something

Judge Denies Musk’s Request to Block OpenAI’s For-Profit Plan

In November, Elon Musk asked a federal court to block OpenAI’s plan to transform itself from a nonprofit into a purely for-profit company. On Tuesday, a federal judge in San Francisco denied Mr. Musk’s request, calling it “extraordinary.” But the court allowed Mr. Musk to proceed with other aspects of a lawsuit he filed last year against OpenAI and its chief executive, Sam Altman. Mr. Musk helped create OpenAI as a nonprofit in 2015, along with Mr. Altman and others. In 2018, Mr. Musk left the organization after a battle for control of the company. Mr. Altman then attached OpenAI

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link

If You are Doing RAG You Need to Know Hypothetical Document Embeddings

Created Using MidJourney An introduction to hypothetical document embeddings(HyDE) as a cornerstone of RAG. The original HyDE paper. Continuing with our series about RAG, today we are going to explore a technique that is often lost in broader RAG implementations but its quite effective. Hypothetical Document Embeddings (HyDE) represents a paradigm shift in the realm of Retrieval-Augmented Generation (RAG), introducing a novel approach to bridging the semantic gap between queries and document corpora. At its core, HyDE leverages the generative capabilities of LLMs to synthesize a hypothetical ideal document that would perfectly answer a given query, prior to initiating the

MySQL At Uber

How does Uber achieve 99.99% availability across 2,000+ MySQL® clusters? Learn how we manage our MySQL fleet at scale, from architecture to control plane optimizations. Source link