Difference between revisions of "Google"
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** [https://cloud.google.com/vision/overview/docs/ Cloud Vision] | ** [https://cloud.google.com/vision/overview/docs/ Cloud Vision] | ||
** [https://cloud.google.com/vision/ Cloud Vision API] - drag & drop picture on webpage | ** [https://cloud.google.com/vision/ Cloud Vision API] - drag & drop picture on webpage | ||
| − | * [[Algorithm Administration#Automated Learning|Automated Learning]] | + | * [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ... [[Algorithm Administration#Automated Learning|Automated Learning]] |
* [https://ai.google/tools/ We’re making tools and resources available so that anyone can use technology to solve problems | Google AI] | * [https://ai.google/tools/ We’re making tools and resources available so that anyone can use technology to solve problems | Google AI] | ||
* [[Dopamine]] - reinforcement learning algorithms | * [[Dopamine]] - reinforcement learning algorithms | ||
Revision as of 20:16, 6 July 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Generative AI ... Conversational AI ... OpenAI's ChatGPT ... Perplexity ... Microsoft's Bing ... You ...Google's Bard ... Baidu's Ernie
- Google's Tools and Resources
- Vertex AI
- Gato
- Google's Duet AI will bring generative AI to Docs, Sheets, Meet, and more | Elizabeth de Luna - Mashable ... AI will soon materialize in Google's entire Workspace portfolio of apps
- Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)
- Colaboratory (Colab) - Jupyter notebooks
- Hands-on labs
- Google Cloud
- Google Cloud Platform Marketplace
- Google Cloud Code and Google Kubernetes Engine (GKE)
- Pixel phone with TPU - Tensor Processing Unit / AI Chip
- TensorFlow
- TensorBoard ...TensorFlow's visualization toolkit
- TensorFlow Hub is a library for reusable machine learning modules that you can use to speed up the process of training your model. A TensorFlow module is a reusable piece of a TensorFlow graph. With transfer learning, you can use TensorFlow modules to preprocess input feature vectors, or you can incorporate a TensorFlow module into your model as a trainable layer. This can help you train your model faster, using a smaller dataset, while improving generalization.
- Large Language Model (LLM) ... Natural Language Processing (NLP) ...Generation ... Classification ... Understanding ... Translation ... Tools & Services:
- LaMDA (Language Model for Dialogue Applications): our breakthrough conversation technology
- Language Interpretability Tool (LIT) | Google - GitHub
- Google Natural Language
- Google Semantic Reactor
- Bidirectional Encoder Representations from Transformers (BERT)
- Gboard on Pixel phones now uses an on-device neural network for [[Speech Recognition| speech recognition] | Kyle Wiggers - VentureBeat
- Universal Sentence Encoder lite a model that encodes text into 512-dimensional embeddings. These embeddings can then be used as inputs to natural language processing tasks such as sentiment classification and textual similarity analysis. This module is a TensorFlow.js
- AI Platform
- AI Hub - explore and use a variety of AI asset categories. AI Hub offers a collection of components for developers and data scientists building artificial intelligence (AI) systems. Use AI Hub to: [1] Find, deploy, and use Kubeflow Pipelines and components, [2] explore code and learn in interactive Jupyter notebooks, [3] explore and reuse TensorFlow modules, Explore, deploy, and use trained models, [4] use prepackaged virtual machine (VM) images to quickly set up your AI environment, and [5] share AI components with your colleagues.
- Kubeflow Pipelines ML workflows on Kubernetes
- Google AutoML
- Cloud Vision
- Cloud Vision API - drag & drop picture on webpage
- Singularity ... Sentience ... AGI ... Curious Reasoning ... Emergence ... Moonshots ... Explainable AI ... Automated Learning
- We’re making tools and resources available so that anyone can use technology to solve problems | Google AI
- Dopamine - reinforcement learning algorithms
- Google AI Experiments
- ML Engine
- Prediction API
- Grow with Google
- Learn from ML experts at Google
- Google Internet of Things (IoT)
- Psychlab ...testing virtual agents in 3D environments
- Deep Reinforcement Learning (DRL) ...Importance Weighted Actor-Learner Architecture (IMPALA)
- Google AIY Projects Program ... connect Vision or Voice Kit to a Wi-Fi network right from mobile device
- Android Neural Networks API ...machine learning on Android devices
- Big\Table ...designed with a storage engine for machine learning applications leading to better predictions
- Pub/Sub ...messaging and ingestion for event-driven systems and streaming analytics.
- BiqQuery ML (BQML) ...enables users to create and execute machine learning models in BigQuery by using standard SQL queries.
- Firebase ...mobile and web functionality like analytics, databases, messaging and crash reporting
- DialogFlow ...creating conversational AI applications, including chatbots, voicebots, and IVR bots
- Google Analytics ...measure your web traffic
- Teachable Machine ...train a computer to recognize your own images, sounds, & poses
- Google Coral ...toolkit to build products with local AI. Our on-device inferencing capabilities
- Google Sheets ...access, create, and edit your spreadsheets wherever you go — from your phone, tablet, or computer
- Google Facets ...contains two robust visualizations to aid in understanding and analyzing machine learning datasets
- DeepMind - Open Source
- People + AI Research (PAIR) ... devoted to advancing the research and design of people-centric AI systems.
- Towards a Human-like Open-Domain Chatbot | D. Adiwardana, M. Luong, D. So, J. Hall, N. Fiedel, R. Thoppilan, Z. Yang, A. Kulshreshtha, G. Nemade, Y. Lu, Q. Le - arCXiv - Cornell University ... We present Meena, a multi-turn open-domain chatbot trained end-to-end on data mined and filtered from public domain social media conversations. This 2.6B parameter neural network is simply trained to minimize perplexity of the next token.
Google has been developing AI for more than two decades. Some of their most popular products like Lens and Translate were built entirely using artificial intelligence technologies like optical character recognition and machine learning. Google has long relied on Artificial Intelligence-related resources to power, improve, and enhance its core products such as the Google search engine, voice search, and its photos app.
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The Path From Cloud AutoML to Custom Model (Cloud Next '19)
by Sara Robinson
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