Systems & Languages


r/MachineLearning - [R] Neural Architecture Optimization

#artificialintelligence

Abstract: Automatic neural architecture design has shown its potential in discovering powerful neural network architectures. Existing methods, no matter based on reinforcement learning or evolutionary algorithms (EA), conduct architecture search in a discrete space, which is highly inefficient. We call this new approach neural architecture optimization (NAO). There are three key components in our proposed approach: (1) An encoder embeds/maps neural network architectures into a continuous space. The performance predictor and the encoder enable us to perform gradient based optimization in the continuous space to find the embedding of a new architecture with potentially better accuracy.


Macron Says Europe's Security Architecture Must Be Rethought

U.S. News

French President Emmanuel Macron says "we must rethink the European security architecture" as he pushed for a continent-wide effort to create "a strategic partnership, including in terms of defense, with our closest neighbors.".


Discovering Latent Information By Spreading Activation Algorithm For Document Retrieval

arXiv.org Artificial Intelligence

Syntactic search relies on keywords contained in a query to find suitable documents. So, documents that do not contain the keywords but contain information related to the query are not retrieved. Spreading activation is an algorithm for finding latent information in a query by exploiting relations between nodes in an associative network or semantic network. However, the classical spreading activation algorithm uses all relations of a node in the network that will add unsuitable information into the query. In this paper, we propose a novel approach for semantic text search, called query-oriented-constrained spreading activation that only uses relations relating to the content of the query to find really related information. Experiments on a benchmark dataset show that, in terms of the MAP measure, our search engine is 18.9% and 43.8% respectively better than the syntactic search and the search using the classical constrained spreading activation. KEYWORDS: Information Retrieval, Ontology, Semantic Search, Spreading Activation


The Scalable Neural Architecture behind Alexa's Ability to Select Skills : Alexa Blogs

#artificialintelligence

Alexa-like voice services traditionally have supported small numbers of well-separated domains, such as calendar or weather. In an effort to extend the capabilities of Alexa, Amazon in 2015 released the Alexa Skills Kit, so third-party developers could add to Alexa's voice-driven capabilities. We refer to new third-party capabilities as skills, and Alexa currently has more than 40,000. Four out of five Alexa customers with an Echo device have used a third-party skill, but we are always looking for ways to make it easier for customers to find and engage with skills. For example, we recently announced we are moving toward skill invocation that doesn't require mentioning a skill by name.


Inception Network Deep Learning Architecture

#artificialintelligence

Inception Network Deep Learning Architecture Sharing some of my experience on simplifying the cost & how to go with best combination of hyper parameters.


Linked List Data Structure using Python Udemy

@machinelearnbot

Get your team access to Udemy's top 2,500 courses anytime, anywhere. If you have started using Python, by now you must have come to know the simplicity of the language. This course is designed to help you get more comfortable with programming in Python. It covers completely, the concept of linked list using Python as the primary language. You need to be equipped with the basics of Python such as variables, lists, dictionary and so on.


Sustainable Deep Learning Architectures require Manageability

#artificialintelligence

This is a very important consideration that is often overlooked by many in the field of Artificial Intelligence (AI). I suspect there are very few academic researchers who understand this aspect. The work performed in academe is distinctly different from the work required to make a product that is sustainable and economically viable. It is the difference between computer code that is written to demonstrate a new discovery and code that is written to support the operations of a company. The former kind turns to be exploratory and throwaway while the the latter kind tends to be exploitive and requires sustainability.


Import AI: #90: Training massive networks via 'codistillation', talking to books via a new Google AI experiment, and why the ACM thinks researchers should consider the downsides of research

#artificialintelligence

Training unprecedentedly large networks with'codistillation': …New technique makes it easier to train very large, distributed AI systems, without adding too much complexity… When it comes to applied AI, bigger can frequently be better; access to more data, more compute, and (occasionally) more complex infrastructures can frequently allow people to obtain better performance at lower cost. One limit is in the ability for people to parallelize the computation of a single neural network during training. To deal with that, researchers at places like Google have introduced techniques like'ensemble distillation' which let you train multiple networks in parallel and use these to train a single'student' network that benefits from the aggregated learnings of its many parents. Though this technique has shown to be effective it is also quite fiddly and introduces additional complexity which can make people less keen to use it. New research from Google simplifies this idea via a technique they call'codistillaiton'.


Global Bigdata Conference

#artificialintelligence

Blockchain is a technology that everybody seems to think will revolutionize the global economy. If nothing else, the cryptocurrency boom has produced a flood of VC money that's trying to cash in on every potential application for this distributed hyperledger technology. It's no surprise that the artificial intelligence (AI) community is also trying to board the blockchain train. Blockchain as an AI compute-brokering backbone: AI developers need the ability to discover, access, and consume distributed computing resources when preparing, modeling, training, and deploying their applications. The Cortex blockchain allows users to submit bids, in the form of AI "smart contracts," for running AI algorithms in a distributed, trusted on-demand neural-net grid.


Invacio Invest ICO – We are working to resolve some of the world's most complex and recalcitrant problems using our original distributed artificial intelligence systems

#artificialintelligence

The following Agreement is split into two elements: (i) a "Subscription Agreement" relating to the sale of Invacio Tokens (Block-chain Tokens), referred to as'Coins' or'Invacio Coins'; and (ii), a second element relating to the'Gifting' of Invacio Holdings (UK) Ltd C-Class Stock ("Class C Shares", "Class C" or "C shares") allocations via their current Offshore Holding Corporation Invacio (AAP) Holdings Ltd, The Share Gifting is Equity in the the Main UK Limited Company, by William J D West, CEO of Invacio, thus it's holding companies and subsidiaries, Enterprises or Ventures are included in the Gifting as full assets of Invacio Holdings (UK) Ltd .