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AIStop Failing Interviews. Use Google AI instead. 🤖📈 #aitools #viralvideos #artificial #trendingreels #uk🇬🇧
@aisecretswithfawad
#Unsupervised Learning Vs Supervised Learning
Assista vídeos de Reels sobre Unsupervised Learning Vs Supervised Learning de pessoas de todo o mundo.
Assista anonimamente sem fazer login.
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Reels em Alta
(12)
108
TEAI interview questions#ai #interviewquestions #genai #interview #googlecloud
@techtrapture
124.1K
KAComment “link” and I’ll send you the resource which has all the important topics you need to study for AI/ML interviews
#viral #tech #ai #ml #jobhunt
@kareema.changezy
966
RIGoogle is no longer just a search engine 🤯
It’s becoming an AI language engine powered by Gemini.
Save this reel before Google changes the rules again 🚀
Google Little Language Lessons, Little Language Lessons site, Google AI language learning, AI language tool Google, Tiny Lesson vocabulary, Slang Hang practice, Word Cam translator, Google language AI experiment, learn languages with AI
@richmeetings.ai
109.0K
NIComment "SKILLS" to get this new AI Learning Platform from Google.
Google just dropped Google Skills. It's a huge free platform. Over 3,000 AI courses. Made by experts at Google and DeepMind.
Think of it like a personal trainer for your career. It teaches the exact AI skills jobs need now. And in the future.
The good news? It has everything. From super basic stuff. To advanced builds.
Start here. AI prompting basics. Like telling ChatGPT what to do. Clear and simple.
Then level up. Learn ethical AI. Handle data with tools like TensorFlow. Or set up no-code automations.
Want pro level? Build your own language model. Fine-tune it. Add image gen or predictions. Like crafting a custom robot for your apps.
They added AI Boost Bites too. Quick 10-minute lessons. Perfect for busy days. I recently tried one on prompt tricks. Asked it to fix my Python code. Boom. Fixed in seconds.
Here's what you'll pick up fast:
1. Prompt better for marketing or code
2. Automate browser tasks like a pro
3. Test new AI tools without hassle
Most courses? Totally free. Like free coffee on the house.
Subscribe if you want more. Get official Google certificates. Skill badges for your resume. Proof you know your stuff.
Split long projects into bits. Even if a lesson feels tough. Keep going. You got this.
It's like having Google experts in your pocket. For developers building GitHub repos. Or no-code apps. Hands-on projects. Fresh updates on new models.
The pressure to learn AI? Real. But this makes it easy. Jump in today.
#googleskills #googleai #googledeepmind #aicourses #ailearning
@nick_saraev
3.2K
DEBREAKING: Google just released 10 free AI courses
If there’s one thing to do in 2026, it’s to get AI certified.
Not just for the badge. So you can actually use it at work.
Here are 10 free Google courses worth taking:
1. Introduction to Generative Al
• Understand what Generative AI actually is and how it works.
• Learn how to build simple AI applications using Google tools
2. Introduction to Large Language Models
• Get a clear understanding of models like ChatGPT.
• Learn where LLMs are used, why they matter, and how they can be improved, without heavy tech terms.
3. Introduction to Responsible Al
• Learn how AI can be built ethically.
• Explore Google’s 7 core principles for creating fair, safe, and responsible AI systems.
4. Prompt Design in Vertex Al
• Learn how to write better prompts to get better results from AI.
• Practice creating text and images using Google’s AI tools with hands-on exercises.
5. Introduction to Image Generation
• Understand how AI creates images from scratch.
• Learn the core ideas behind modern image-generation models.
6. Encoder-Decoder Architecture
• Learn how AI translates languages, summarizes content, and generates text.
• A simple introduction to the backbone of language models.
7. Attention Mechanism
• See how AI learns to focus on important information in text and images.
• A quick and clear intro to one of the most important AI concepts.
8. Transformer Models and BERT Model
• Understand the models that changed modern AI.
• Learn how BERT understands context in language, and earn a digital badge on completion.
9. Create Image Captioning Models
• Build AI models that can understand images and describe them in words.
• Learn how vision and language work together.
10. Introduction to Generative Al Studio
• Explore Google’s platform for building AI applications.
• See real demos that show how ideas turn into working AI tools.
Which one are you starting with?
Let's make 2026 your best year ever!
#decodingworklife #careergrowth✨️ #googlecourses #workreels #corporatecommunication
@decodingworklife
1.5K
AIGoogle Meet just killed language barriers in real time 😳🌐
Google is rolling out live AI translation inside Google Meet, powered by Gemini.
It listens as you speak, translates instantly, and preserves tone and expression so conversations still feel human.
Launching in beta for English ⇄ Spanish, with more languages coming soon.
This isn’t subtitles.
This is real-time understanding.
Follow @startuprevenue.ai & @aitechadvice for the biggest AI breakthroughs before they go mainstream 🚀
Save this. Meetings just went global
Google Meet AI translation, Gemini live translation, real-time video call translation, AI language technology, multilingual communication tools, business communication AI, live speech translation
#startuprevenue #aitech #googlemeet #aiinnovation #futureofwork languageai communicationtech productivitytools reelsviral nextgen aiworld technews digitalfuture
@aitechadvice
52.9K
AB💬Comment “Handbook” and I’ll DM it to you.
As 90% of people still don’t know about the free prompt handbook built by Google engineers.
.
.
.
India AI impact summit 2026, AI tools, Prompt engineering, Google AI, Google prompt guide, Gemini AI, ChatGPT prompts, AI productivity, AI workflows, Advanced prompting, LLM prompting, AI for marketing, AI for startups, AI for students, Generative AI, AI hacks, AI resources, AI automation, Future of AI
@abhinavagr180
76.8K
ITComment "Link" if you want to learn GenAI 👇🏻
Hey, my name is Anu Sharma, and I have been a software engineer at Google.
Google just made every software engineer an AI engineer.
And if you're not preparing for this shift, you're already behind 👇🏻
I saw it happen in real time. Every engineer at Google had to upskill or risk becoming irrelevant.
These weren't optional nice-to-haves. These were survival skills.
Here are the 7 AI skills every Google engineer had to learn:
1. Machine Learning Fundamentals
Not just theory. Real ML pipelines, model training, evaluation metrics.
2. Deep Learning & Neural Networks
CNNs, RNNs, backpropagation, optimization algorithms.
3. Generative AI (GPT, Gemini models)
How these models work, how to fine-tune them, how to deploy them.
4. Natural Language Processing
Tokenization, embeddings, sentiment analysis, text generation.
5. Computer Vision
Image classification, object detection, segmentation, real-world applications.
6. Large Language Models (LLMs)
Prompting, RAG systems, context windows, scaling challenges.
7. Transformers Architecture
Attention mechanisms, encoder-decoder models, the foundation of modern AI.
But here's the thing: learning theory is useless without proof of work.
Google didn't care if you watched tutorials. They cared if you could ship AI-powered features into production.
Projects. Real datasets. Working demos. That's what gets you hired in 2026.
Simplilearn's AI Engineer Course is one I've seen people recommend because it's not just theory.
Python, TensorFlow, PyTorch, OpenAI models—they teach you the actual tools companies use, and you build real projects that prove you can do the work.
I've linked it in my bio if you want to check it out.
Either way, start building. That's what matters.
The AI shift isn't coming. It's already here.
If you've reached here, follow @its.anu.sharma for more real talk about AI, tech careers, and what's actually happening inside big tech.
[google, ai engineer, software engineer, machine learning, deep learning, generative ai, llm, career shift, tech skills, upskilling, anu sharma, simplilearn]
#googleai
#aiengineer
#machinelearning
#genai
#techcareers
@its.anu.sharma
42
GEHow to become Google Conversational AI Developer
@genai_guru
1.8K
PAGoogle is building an AI ecosystem which is going to be more powerful than any other single open source LLMs.
What are your thoughts on this ?
@parushi.yaps
685.2K
HAGoogle and AI are completely different, and understanding how they work changes how you use them.
*To be specific: by “AI” here I mean Large Language Models, or LLMs. Google has technically always been AI – its PageRank algorithm, which decides which links to return to you, has always been a form of AI. And yes, Google is now augmented with LLMs. What we’re comparing in this post is traditional Google (using PageRank) and LLMs.*
Lets break down the differences in plain English & answer some of the most commonly asked questions below (so you know when to use which tool):
Q: What’s the biggest difference between Google and LLMs like ChatGPT?
Google searches. LLMs predict.
Google scans the internet and returns the most relevant websites using a ranking system.
LLMs don’t search. They learn from massive amounts of text — and then predict what word comes next based on probability.
Q: So are LLMs just looking things up?
No. They’re word generators. They learn patterns in language, and then generate text that follows those patterns.
That’s why they can sound confident — even when they’re wrong.
Many - crucially, not all!!! - models today have been augmented with the ability to pull some data from the internet and insert it into its context window (i.e. the input into the LLM, the prediction machine) which reduces the risk of “hallucination,” (i.e. making things up) but even so, the model is still a predictor. It can (and often does) still mess up EVEN with web search added.
Q: What’s the biggest tradeoff to watch out for?
Hallucinations. LLMs are generators (& not a fact checkers). So they can make things up.
That’s why tools like web-browsing and retrieval-augmented generation (RAG) are so important. They anchor generation to real data. But they’re not foolproof.
Bottom line:
If Google is a librarian,
LLMs are improv actors who’ve read the entire library.
Sometimes brilliant. Sometimes also wrong.
But when you understand *how* they think — you can use them way more effectively.
Leave your questions or comments in the section below 🥰👇 & share to spread the word!! This concept is simple and yet so important. You guys rock, sending love to you all!
@harpercarrollai
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