stock exchange evolution panel

AI & Machine Learning News. 20, August 2018

This startup is raising $750 million to outmaneuver Domino’s and Pizza Hut with pizzas made by robots

Robots could kill off jobs in the future – but at least they come bearing pizza. Founded in 2015, Zume Pizza uses robotics and artificial intelligence to make pizza more quickly. Machines press mounds of dough, squirt and spread sauce, and lift pizzas in and out of the oven, in a fraction of the time it would take human workers to do the same.

Now SoftBank is in talks to invest up to $US750 million in Zume,Bloomberg reports. The cash infusion could help ramp up the pizza delivery company’s side hustle, creating technology for other restaurants that want to get into the automated food truck game. An increasing number of pizza eaters are ditching legacy brands like Domino’s and Pizza Hut for newer fast-casual and delivery chains. In 2016, Business Insider toured Zume’s headquarters in Mountain View, California, to see if the pizza is as good as its tech.
2018-08-09 00:00:00 Read the full story.
CloudQuant Thoughts… I cannot believe we missed this story last week, possibly the most important tech story of the last 10 years. I am going to go and shoot my AI robotic ML based web-scraper. Wait, it has told me I am wrong, that this story does not contain Machine Learning or Artificial Intelligence data. OK. OK. I need a pizza!

 

How to create a virtuous cycle of data with your customers

Over the last decade, technology companies like Amazon, Apple, Google, and Facebook have risen to the top of brand value lists by outgrowing many of the traditional consumer companies like Disney, Toyota, and McDonald’s. There are many factors driving this rapid growth in tech brand value, but a large portion of the growth can be attributed to the virtuous cycle of data for tech companies. Technology companies know their customers, even anonymously, much better than the companies behind traditional consumer products, and they use that customer data to continuously improve their products which, in turn, drives brand affinity and loyalty.
2018-08-19 00:00:00 Read the full story.
CloudQuant Thoughts… One man’s virtuous circle is another man’s descending spiral consuming creativity. Amazon farming data from sales of independent products, so that they can create their own lines of AMAZON BASICS, is just destroying the original creators. Eventually, you end up with no creativity. How is that good for anyone? But this article contains the answer to the most asked model development question of all, “How do I come up with an idea for a trading system?”. The shift from the top 5 brands in 2006 to the top 5 in 2017 mentioned near the top of this article immediately got my juices flowing. How do you predict/detect a shift like this? Can we look back and see how/when it happened? Can we code up a model to detect those moves? Will it pick out some other movers and shakers? Do you think you can do it? Perhaps you can utilize ML and AI. Try it out using CloudQuant.

 

Yewno Launches Blockchain Index in Partnership with STOXX

Last week, Yewno announced that it had launched the iSTOXX Yewno Developed Markets Blockchain Index, the second index it has released in partnership with STOXX. In January, Yewno launched the STOXX AI Global Artificial Intelligence Index leveraging its AI based algorithm.

The creation of the iSTOXX Yewno Developed Markets Blockchain Index leverages Yewno’s artificial intelligence technology and an underlying dynamic knowledge graph which aggregates a large volume of structured and unstructured data in order to identify companies that are exposed to Blockchain technology and research. The selection of companies included in the index spans multiple sectors and industries, and each component is selected based on the highest exposure to Blockchain technology.
2018-08-20 02:30:37+00:00 Read the full story.
CloudQuant Thoughts… Another example of finding the potential future leaders in the markets, this time based on their investment in AI and Blockchain technology. But I cannot imagine that AI and ML are needed to pick these companies out. Also, where there are leaders there are also laggards so the opposing theory is an optional play. Can you come up with a basket of Tickers that are in a hot sector or their opposing cooler competitors? Can you code up a model to test trade them? Head over to CloudQuant and give it a go.

 

D.E. Shaw Dives Into Machine Learning

The D. E. Shaw group, a global investment and technology development firm and a pioneer in quantitative approaches to trading and investment, today announced the formation of a new, independent machine learning research and development effort.

The new Machine Learning Research Group, which will operate in parallel to the firm’s longstanding machine learning efforts, will be overseen by Dr. Pedro Domingos, who will join the firm as a Managing Director. Dr. Domingos will report to Cedomir Crnkovic, Managing Director, who joined the firm in 1997 and for much of his tenure ran the firm’s futures and curren…
2018-08-16 10:33:39-04:00 Read the full story.
CloudQuant Thoughts… D.E. Shaw is a very successful global investment management firm. They use quantitative analysis, algorithmic trading and applied mathematical techniques for investment management. With over a decade of Machine Learning experience, they reportedly are using alternative data sets to seek out new alpha signals and to enhance their fundamental research.

D.E. Shaw is often compared with Renaissance Technologies and AQR Capital Management. These firms are leading the trading and investment industry in the use of mathematical models and computers to plot out trading techniques.

Innovation is the name of the game at D.E. Shaw.

 

Patent Application : Drone delivery of coffee based on a cognitive state of an individual…

Coffee or other drink, for example a caffeine containing drink, is delivered to individuals that would like the drink, or who have a predetermined cognitive state, using an unmanned aerial vehicle (UAV)/drone. The drink is connected to the UAV, and the UAV flies to an area including people, and uses sensors to scan the people for an individual who has gestured that they would like the drink, or for whom an electronic analysis of sensor data indicates to be in a predetermined cognitive state. The UAV then flies to the individual to deliver the drink.

Patent Application

CloudQuant Thoughts… Beaten to it by BizarroComics.com in 2014

Image result for coffee by drone cartoon

 

Tech Moves: NFL tight end joins Amperity; Vision Critical founder launches Rival Technologies; and more

Amperity, the Seattle-based customer data platform, has hired a sports star for its sales team. NFL tight end Cooper Helfet has joined the company to lead its efforts in sports and entertainment, Amperity CEO Kabir Shahani told GeekWire in an email.

“Cooper is extraordinarily talented and brings to Amperity the championship mindset that has allowed him to achieve at the highest levels in the NFL,” Kabir Shahani told GeekWire in an email. “That mental game is a huge asset both for his professional success in a post-NFL career, and for our organization broadly.”
2018-08-14 13:00:40-07:00 Read the full story.
CQ Thoughts… We wonder what the electronic trading experts at Rival Systems think about the name Rival Technologies?

 

Alexa and Cortana may be working together, but the smartphone is still king

After nearly a year of waiting, Amazon and Microsoft this week brought Alexa to Windows 10 PCs and Cortana to Echo speakers. Overnight, the move delivered Cortana to millions of Echo speakers and Alexa to hundreds of millions of personal computers in the United States. The Echo line of smart speakers continues to enjoy the largest market share, and Windows 10 is installed on nearly 700 million computers.

The partnership was made in recognition of the fact that we live in a multi-assistant world. “The world is big and so multifaceted. There are going to be multiple successful intelligent agents, each with access to different sets of data and with different specialized skill areas. Together, their strengths will complement each other and provide customers with a richer and even more helpful experience,” Amazon CEO Jeff Bezos said in a statement when the partnership was announced last August.
2018-08-17 00:00:00 Read the full story.
CloudQuant Thoughts… This seems like a big win for Amazon and a loser for Microsoft. Who is going to call on Cortana on their Amazon Echo device?

 


Below the Fold.

 

Bank of England chief economist warns on AI jobs threat

The chief economist of the Bank of England has warned that the UK will need a skills revolution to avoid “large swathes” of people becoming “technologically unemployed” as artificial intelligence makes many jobs obsolete.

Andy Haldane said the possible disruption of what is known as the Fourth Industrial Revolution could be “on a much greater scale” than anything felt during the First Industrial Revolution of the Victorian era.

2018-08-20 00:00:00 Read the full story.

 

WaveSense’s ground-penetrating radars could make self-driving cars safer

Radar. Lidar. Cameras. They’re the components that help give autonomous vehicles from Uber, GM’s Cruise Automation, Google spinoff Waymo, and countless others a sense of their surroundings. But WaveSense CEO Tarik Bolat thinks they have a blind spot.

“A massive transformation in transportation and mobility is underway around the world as autonomous systems advance at an unprecedented pace,” Bolat said. “But before broad adoption of self-driving vehicles can occur, navigation safety and reliability must improve significantly, particularly in adverse weather conditions like snow, rain, and fog.”

2018-08-20 00:00:00 Read the full story.

 

Recent Advances for a Better Understanding of Deep Learning − Part I

I would like to live in a world whose systems are build on rigorous, reliable, verifiable knowledge, and not on alchemy. […] Simple experiments and simple theorems are the building blocks that help understand complicated larger phenomena.

This call for a better understanding of deep learning was the core of Ali Rahimi’s Test-of-Time Award presentation at NIPS in December 2017. By comparing deep learning with alchemy, the goal of Ali was not to dismiss the entire field, but “to open a conversation”. This goal has definitely been achieved and people are still debating whether our current practice of deep learning should be considered as alchemy, engineering or science. Seven months later, the machine learning community gathered again, this time in Stockholm for the International Conference on Machine Learning (ICML). With more than 5,000 participants and 629 papers published, it was one of the most important events regarding fundamental machine learning research. And deep learning theory has become one of the biggest subjects of the conference.
2018-08-19 13:23:32.997000+00:00 Read the full story.

 

Lean startup and machine learning – Towards Data Science

The term Lean startup was coined about ten years ago. Since that time it has grown to become one of the most influential methodologies for building startups, especially those that fall in the category of web-based software companies. Lean came of age during the internet revolution. We now sit on the cusp of a different revolution — one ushered in by machine learning algorithms. It is safe to assume that most or all software in the near future will contain some element of machine learning. But how compatible is Lean with machine learning, in principle and in practice? (See here for an interesting perspective)
2018-08-19 22:03:25.287000+00:00 Read the full story.

 

Google, stop trying to sell us AutoML – Hacker Noon

Google’s AutoML is a glaring example of hype over product. Although the field of AutoML has existed for many years now, Google co-opted the term to refer specifically to its neural architecture search and surrounding suite of products. Neural architecture search essentially creates a dataset with various unique, highly specialized architectures; this search is incredibly computationally intensive and is used to find a singular best model for that specific data. Once that specific model has been found, it is relatively worthless to all the other data except the exact data it was trained on as it has been, at huge computational cost, tuned for that specific data and that specific data only.
2018-08-20 11:21:01.413000+00:00 Read the full story.

 

DataHack Radio Episode #8: How Self-Driving Cars Work with Drive.ai’s Brody Huval

Self-driving cars are expected to rule the streets in the next few years. In fact, countries like the USA, China and Japan have already started using them in real-world situations! One of the leaders in this space is Andrew Ng backed Drive.ai, a self-driving car start-up based in California.

So how do these autonomous cars work? How difficult is it making one from scratch? What kind of machine learning techniques are used? In this podcast, Drive.ai’s co-founder Brody Huval sheds light on these questions put forward by Kunal, along with other really intriguing facets of autonomous vehicles. It’s a podcast you better not miss!
2018-08-19 23:11:39+05:30 Read the full story.

 

India Witnesses First Ever Artificial Intelligence Art Show

Nature Morte presents a group exhibition featuring works created entirely by artificial intelligence in collaboration with Harshit Agrawal, Memo Akten, Jake Elwes, Mario Klingemann, Anna Ridler, Nao Tokui & Tom White. Gradient Descent is the first ever art exhibition in India to include artwork made entirely by artificial intelligence.

Curated by 64/1, an art curation and research collective founded by artist Raghava KK and economist Dr. Karthik Kalyanaraman, Gradient Descent, explores the intersection between artificial intelligence and contemporary art. Bringing together artists who address how contemporary art can create a dynamic human-machine relationship, this groundbreaking exhibition provides us with a vision of what art could be in the post-human age.
2018-08-20 12:03:08+00:00 Read the full story.

 

SalesForce Open Sources ML Software That Powers Its Einstein AI

Popular cloud computing giant, SalesForce has announced today that it has open-sourced its machine learning tool TransmogrifAI. This ML tool is the core software behind the company’s in-house AI technology called Einstein. With this, SalesForce has a strong intention of tapping AI solutions to fruition in its customer services and sales business.

2018-08-20 00:00:00 Read the full story.

 

Artificial intelligence is now directly controlling cooling at Google data centers

In Android 9 Pie, Alphabet’s DeepMind division is responsible for machine learning features like Adaptive Battery and Brightness. One of the first collaborations between the two companies was an AI system tasked with increasing energy efficiency at Google’s data centers. Two years later, an AI has been granted direct control over cooling these servers. According to Google, this is the “first-of-its-kind cloud-based control system.” Every five minutes thousands of sensors throughout the data center issue and send readings to the cloud. Deep neural networks then work to “predict how different combinations of potential actions will affect future energy consumption.”

The AI system then identifies which actions will minimize the energy consumption while satisfying a robust set of safety constraints. Those actions are sent back to the data center, where the actions are verified by the local control system and then implemented. This level of automation was something that human operators asked for to implement more granular actions at greater frequency and with fewer mistakes.
2018-08-17 00:00:00 Read the full story.

 

The AI-first startup playbook

Iterative Lean Startup principles are so well understood today that an minimum viable product (MVP) is a prerequisite for institutional venture funding, but few startups and investors have extended these principles to their data and AI strategy. They assume that validating their assumptions about data and AI can be done at a future time with people and skills they will recruit later.

But the best AI startups we’ve seen figured out as early as possible whether they were collecting the right data, whether there was a market for the AI models they planned to build, and whether the data was being collected appropriately. So we believe firmly that you must try to validate your data and machine learning strategy before your model reaches the minimal algorithmic performance (MAP) required by early customers. Without that validation — the data equivalent of iterative software beta testing — you may find that the model you spend so much time and money building is less valuable than you hoped.
2018-08-18 00:00:00 Read the full story.

 

What on earth is data science? The quest for a useful definition : “Data science is the discipline of making data useful.”

Behold my pithiest attempt: “Data science is the discipline of making data useful.” Feel free to flee now or stick around of a tour of its three subfields : Statistics, Machine learning, Data-Mining/Analytics.
The term no one really defined. If you poke around in the early history of the term data science, you see two themes coming together. Allow me to paraphrase for your amusement:

  • Big(ger) data means more tinkering with computers.
  • Statisticians can’t code their way out of a paper bag.

And thus, data science is born. The way I first heard the job defined is “A data scientist is a statistician who can code.” I’ll be full of opinions on that in a moment, but first, why don’t we examine data science itself?…
2018-08-18 19:45:00.019000+00:00 Read the full story.

 

AI Creating Big Winners in Finance

Artificial intelligence is changing the finance industry, with some early big movers monetizing their investments in back-office AI applications. But as this trend widens, new systemic and security risks may be introduced in the financial system. These are some of the findings of a new World Economic Forum report, The New Physics of Financial Services – How artificial intelligence is transforming the financial ecosystem, prepared in collaboration with Deloitte.

“Big financial institutions are taking a page from the AI book of big tech: They develop AI applications and make them available as a ‘service’ through the cloud,” said Jesse McWaters, AI in Financial Services Project Lead at the World Economic Forum. “It is turning what were historically cost centres into new source of profitability, and creating a virtuous cycle of self-learning that accelerates their lead.”
2018-08-16 10:22:10-04:00 Read the full story.

 

TensorFlow 2.0 Is Coming; Here’s What You Should Look Forward To

The eagerly-awaited update for the popular machine learning framework TensorFlow was announced earlier this week by Martin Wicke from Google AI. He announced the news on his Google Group, adding that they are planning to release a preview version of TensorFlow 2.0 in late 2018.

Since its open-source release in 2015, TensorFlow has become one of the most widely adopted ML frameworks, catering to a broad spectrum of users and use-cases. In this time, TensorFlow has evolved along with rapid developments in computing hardware, machine learning research, and commercial deployment.
2018-08-19 12:55:43-04:00 Read the full story.

 

Factory reset: Tech startups raise big bucks to help companies cut waste

Society has become somewhat accustomed to disposable goods, be it cheap garments, budget phones, or plastic packaging.

But with Earth facing untold apocalyptic catastrophes in the decades to come, there has been a growing push to do something — anything — to counter the predicted cataclysmic events that await us.

A few months back, Seattle became the first major U.S. city to ban single-use disposable straws, while England could become the first…
2018-08-18 00:00:00 Read the full story.

 

CFA Institute: 2019 Curriculum Includes Machine Learning, Cryptos

Exam-sitters in the 2019 CFA Program will see additions covering the latest iterations of financial technology, as well as topics like cryptocurrency and machine learning, CFA Institute announced today. The update, spurred by a combination of focus groups and surveys completed by members of the institute, will include 10 new readings and major revisions, as well as improvements to 18 existing readings.

The rationale for the additions and reworkings came down to basic economics: supply and demand. “Our goal is to be a fast-follower,” said Stephan Horan, managing director of credentialing for CFA Institute. “That’s what the industry told us that candidates needed to know.” Candidates will face these new topics along with nearly 9,000 pages of curriculum that takes approximately 1,000 hours, on average, to master. Topics with dialed-down or streamlined coverage are credit default swaps and some aspects of portfolio management, said Horan.
2018-08-15 15:43:19-04:00 Read the full story.

 

CEO CHAT: Bill Stephenson, AIR Summit

Bill Stephenson spent 20 years at Franklin Templeton Investments, ultimately becoming Global Head of Trading and one of the most recognizable figures in the buy-side trading community. After leaving the firm in 2017, he’s now leading the AIR Summit, a buy-side only event focused on showcasing the companies with the most innovative new solutions to help drive alpha.

Traders Magazine editor John D’Antona recently caught up with Stephenson to talk about his new initiative, buy side technology trends, recent market structure developments, and more.
2018-08-15 09:22:10-04:00 Read the full story.

 

9 fascinating things I learned while coding up the rules of a board game

I recently decided I was going to take the rules of the board game Forbidden Island and write them up as code. I guess that sounds like a weird thing to just decide to do, doesn’t it? It’s actually one part of a bigger goal I have at the moment of teaching myself some practical machine learning. As part of this journey, I heard a great idea from YouTuber Jabrils to set yourself a significant challenge that you’re interested in, and to work towards surmounting that challenge. For Jabrils, his challenge was getting an AI to control a Forrest Gump character to run around a course in a game. For my challenge, I’ve decided I’d like to build an AI that can play Forbidden Island. (And win!)

Obviously, if you’re going to have an AI play a game, you first need a digital version of the game for the AI to play. I knew writing up the rules of the game would be a bit of a distraction, but I decided to give it a crack anyway. I’d been making some good progress with the fast.ai machine learning course, but it was hard work and I thought this would be a fun detour.

It ended up taking quite a bit longer than I anticipated. While I was originally only planning to encode the game rules into code, I was eventually seduced by the idea of writing a program that could play the game. Turning my own automatic thoughts while playing the game into code that could automatically execute was quite the challenge. Here’s the top nine things I learned on this journey:

  1. Kotlin is an awesome programming language
  2. The rules of simple games are actually really complex
  3. The written rules of a game may be ambiguous
  4. Humans don’t consider all the possibilities
  5. Our brains are fantastic at matching patterns and ruling out large swathes of options
  6. Getting statistical significance can be really challenging
  7. Simple rules don’t win games
  8. Games are fascinating
  9. There is a computer made of meat in your head and it’s ridiculously powerful

2018-08-17 17:04:01.221000+00:00 Read the full story.

 

How Figure Eight Speeds Up Machine Learning With Video Object Tracking

It generally takes a lot of reps (repetitions) for a human to become really good at something. Playing the violin, swinging at (and hitting) a hard-thrown baseball and dropping back to complete a long pass in football are examples of this.

Similarly, it takes a machine a lot of reps to be able to remember a data set and then bring it to the fore when someone needs the information. A lot of people don’t realize this.

San Francisco-based startup Figure Eight knows all about this practice and specializes in teaching artificial intelligence engines how to perform optimally, and it does this through video reps.

Figure Eight, which describes its product as a “human-in-the-loop machine learning platform,” on Aug. 14 launched its ML-assisted Video Object Tracking solution to accelerate the creation of training data for customers in key industries such as automotive and transportation, consumer goods and retail, media and entertainment, and security and surveillance.
2018-08-14 00:00:00 Read the full story.

 

Intel Unveils Data Center Processor Plans Through 2020 : Cooper Lake….

Chip giant Intel’s (NASDAQ:INTC) second-largest business by both revenue and operating profit, and arguably its most important business from a growth perspective, is its data center group, or DCG for short. Last quarter, DCG saw revenue and operating profit grow 27% and 64.8%, respectively.

Their new processor, Cooper Lake, will also support the bfloat16 numeric format, which the executive says “is principally used for [machine learning] training kinds of workloads.”

Earlier in Shenoy’s presentation, the executive disclosed that the company sold over $1 billion worth of its Xeon processors to customers looking to run artificial intelligence workloads. In a separate presentation, Intel executive Naveen Rao said that the market opportunity for data center processors sold to run artificial intelligence workloads would grow from $2.5 billion in 2017 to between $8 billion and $10 billion by 2022. Although Intel has made it clear that it’s designing chips specifically to run artificial intelligence workloads , the company has said that it’s “reinventing Xeon for [artificial intelligence]” via a combination of hardware and software advancements.
2018-08-20 00:45:11-04:00 Read the full story.

 

Qualcomm Snapdragon 670 SoC Adds AI to Smartphones

Today’s topics include the Qualcomm Snapdragon 670 bringing AI to mainstream mobile phones, and Dell EMC targeting AI workloads with integrated systems.

2018-08-15 00:00:00 Read the full story.

 

Breaking News founders launch Factal, delivering real-time news and incident alerts to companies

When NBC News shut down its popular Breaking News website and app in late 2016, the team heard not just from general news consumers but also from disappointed users at big companies and organizations around the globe. They had come to rely on the service for 24/7 real-time news and incident updates to protect employees and assets from threats around the globe.

Users can set up custom notifications depending on factors including the location of their facilities and assets. Factal then uses machine learning technology and editors to verify and geo-locate information about everything from wildfires to shootings.
2018-08-14 13:00:59-07:00 Read the full

 

Salesforce plans to open-source the technology behind its Einstein machine-learning services

Salesforce is open-sourcing the method it has developed for using machine-learning techniques at scale — without mixing valuable customer data — in hopes other companies struggling with data science problems can benefit from its work.

The company plans to announce Thursday that TransmogrifAI, which is a key part of the Einstein machine-learning services that it believes are the future of its flagship Sales Cloud and related services, will be ava…
2018-08-16 13:00:09-07:00 Read the full story.

 

Why Python Continues to Be the Swiss Army Knife of Programming

Last winter, one of the world’s largest coding bootcamps, Coding Dojo, released an objective analysis of the most in-demand programming languages of 2018.

Coding Dojo came to its findings by analyzing the hundreds of thousands of job postings that contained the name of a programming language on job search engine Indeed.com. It found—to no one’s surprise—that Java is the most in-demand, followed by Python and JavaScript.
2018-08-16 00:00:00 Read the full story.

 

Understanding Probability Theory with Dungeons and Dragons

Probability theory is a rich branch of mathematics that also intersects with philosophy, theology and logic. Probability theory has its roots in the 1600s, when mathematicians Pascal and Fermat began to analyse the mathematics of games of chance. Pascal and Fermat contributed to not only mathematics, but philosophy and theology. Theologians and philosophy majors may recall Pascal’s wager, which in simple terms frames that humans effectively bet with their lives as to whether god exists. We can see therefore, the wide-ranging impact of probability theory.

We can consider that probability theory is a vast area to cover, but one that I believe can be both intuitive and easy to grasp, provided helpful examples are given. Probability theory is also an integral part of data science and understanding the basics in this area will provide a strong foundation for more advanced topics, such as regression and Bayesian analysis.
2018-08-19 21:43:29.884000+00:00 Read the full story.

 

Numpy With Python For Data Science – Hacker Noon

In Part 1 of the Data science With Python series, we looked at the basic in-built functions for numerical computing in Python. In this part, we will be taking a look at the Numpy library.

NumPy is the fundamental package for scientific computing with Python. It contains among other things:

  • a powerful N-dimensional array object
  • sophisticated (broadcasting) functions
  • tools for integrating C/C++ and Fortran code
  • useful linear algebra, Fourier transform, and random number capabilities

2018-08-20 10:51:01.656000+00:00 Read the full story.

 

Python for data science : Part 4 – Towards Data Science

In Part 3 of the Python for data science series, we looked at the pandas library and it’s most commonly used functions — reading and writing files, indexing, merging, aggregating, filtering etc. In this part, we will continue to deep dive further into the Pandas library and look at how it can be used along with other Python functions for querying dataframes.

2018-08-19 21:42:45.990000+00:00 Read the full story.

 

Deep Dive into Math Behind Deep Networks – Towards Data Science

Nowadays, having at our disposal many high-level, specialized libraries and frameworks such as Keras, TensorFlow or PyTorch, we do not need to constantly worry about the size of our weights matrices or remembers formula for the derivative of activation function we decided to use. Often all we need to create a neural network, even one with a very complicated structure, is a few imports and a few lines of code. This saves us hours of searching for bugs and streamlines our work. However, the knowledge of what is happening inside the neural network helps a lot with tasks like architecture selection, hyperparameters tuning or optimisation.

2018-08-17 21:44:15.278000+00:00 Read the full story.

 

Report: Top 10 Well-Funded AI Startups to Watch in 2018

Artificial intelligence (AI) continues to redefine how technology is applied to modern use by the mankind. From recruitment resume screening to the complex Quantum Computing applications, AI has come a long way in causing an optimistic change. Sensing the huge disruption AI is capable to make, funding in the AI sector has climbed steadily and impressively over the past decade. In 2017 alone AI industry saw investors pumping nearly $5 billion in US-based AI startups. As trends point out, 2018 will be a promising year for venture investing in AI startups. AI funding is not restricted to Series A, B or C rounds but rather has progressed to supergiant rounds.
2018-08-17 09:20:09+05:30 Read the full story.

 

CognitiveScale chosen by Dell to Assist Customer Experiences through AI

CognitiveScale Inc., a provider augmented intelligence and AI software, is being selected by Dell to help transform customer experience and marketing productivity through AI. Dell chose CognitiveScale and its Cortex 5 software to power and transform the core of their customer journeys.

By leveraging the power of AI to understand declared, observed, and inferred customer behavior across various channels and devices, CognitiveScale will enable Dell to generate additional insights from customer interactions and create highly personalized experiences. This AI powered system will also deliver prescriptive insights for sales, marketing, and customer service teams to better manage customer engagement.
2018-08-14 00:00:00 Read the full story.

 

Three Hot Trends Warren Buffett Is Missing Out On — But You Don’t Have To

You have an investing advantage over Warren Buffett. No, seriously, you really do. Buffett has admitted that he regrets not buying Google parent Alphabet (NASDAQ:GOOG) (NASDAQ:GOOGL) and Amazon.com years ago. And he’s only been a big buyer of Apple stock in the past few years. Apple gained more than 2,000% in the 10 years before Buffett’s Berkshire Hathaway jumped aboard.

The reality is that Buffett doesn’t invest in what he doesn’t understand. That means he can miss out on some of the hottest trends — at least for a while. And therein lies your advantage: gaining an understanding of trends relatively early on and buying the best stocks to profit from those trends. Here are three hot trends that Buffett is missing out on, along with investing ideas for each one.

  1. Artificial intelligence
  2. Cannabis
  3. Gene editing

2018-08-19 00:00:00 Read the full story.

 

It Turns Out Amazon’s Alexa Isn’t a Great Way to Buy Stuff

Smart-speaker sales are expected to hit 100 million units this year, and reach 225 million units by the end of 2020. Amazon’s Alexa-enabled devices own two-thirds of the smart-speaker market, while Google has about a 30% share. Yet despite these devices’ proliferation, people aren’t really using them to buy stuff, nor does it seem they really want to.

The tech news website The Information reports that out of some 50 million Alexa users, only 1 million have tried to buy something with the device. And of that total, just 100,000 completed a transaction. Amazon disputed those figures, saying that “millions of customers use Alexa to shop.” But it seems that people are more interested in using their devices for listening to music and other entertainment, controlling other connected devices like the lights or the TV, and checking the weather.
2018-08-20 00:00:00 Read the full story.

 

Video : AI Use Cases in Capital Markets

Josh Sutton, CEO of startup AI marketplace Agorai, discusses use cases on how artificial intelligence is transforming capital markets, in both the front and back office.

2018-08-16 14:56:53-04:00 Read the full story.

 

Is NVIDIA Corporation a Buy?

Investors who follow the technology industry closely have likely heard a lot about the graphics processor maker NVIDIA Corporation (NASDAQ:NVDA) over the past few years. That may be because the company’s shares are up more than 950% over the past three years, and because it’s benefiting from the growth of emerging technologies including artificial intelligence (AI) and autonomous vehicles.
2018-08-20 00:00:00 Read the full story.

 

Neurala Announces Brain Builder “AI for Good” Competition for Developers

Following the announcement of its Brain Builder beta program, Neurala, the award-winning artificial intelligence company, today announced a call for submissions for its “AI for Good” competition.

Developers who participate in the “AI for Good” contest will have the chance to win a $1,000 first-place cash prize. The second-place finalist will win an EVGA GeForce GTX 1080 Ti SC2, and the third-place winner will receive a DJI phantom 3. Entries will be judged by a panel of industry experts. Neurala’s own applications and commitment to this theme include its work with Motorola Solutions’ first responder body cams to help find missing children, as well as its partnership with the Lindbergh Foundation to help combat animal poaching in Africa.
2018-08-16 16:00:44-04:00 Read the full story.

 

How humans can communicate with aliens

Stephen Wolfram is an expert in computer languages. And he has an interesting theory on how we may discover that what we learn from computer and artificial intelligence, could ultimately help us communicate with intelligent alien life.
2018-08-16 00:00:00 Read the full story.

 

Tech firms say A.I. can transform health care as we know it. Doctors think they should slow down

As an industry reliant on patient records and beset by outdated technology, health care is widely thought to be a prime target for an artificial intelligence revolution.

Many believe the technology will provide a host of benefits to clinical practitioners, speeding up the overall experience and diagnosing illnesses early on to identify potential treatment.
2018-08-17 00:00:00 Read the full story.

 

Artificial Intelligence in Medicine Gains Massive Traction with Growing Investment in AI in the Space

Many industries across the globe have been disrupted by the influx of artificial intelligence (AI). And the healthcare industry is no different. The technology has far-reaching implications across the different areas of healthcare, including the discovery and development of better medicines, effective prescription of medicines, accurate monitoring of patient adherence to prescription, proper diagnosis of diseases at an early stage, clinical research studies and applications that support decision-based medical tasks, and others.

Given the enormous potential of AI in medicine, the adoption of AI technology by many pharmaceutical and biotechnology companies grew considerably over the past few years, which is leading to the growth of the AI in medicine market. Moreover, the lack of skilled healthcare professionals, the increased funding for the R&D activities concerning the use of AI in medicine, the growing importance of precision medicine fuel the growth of the industry.
2018-08-14 00:00:00 Read the full story.

 

Apple is beefing up a team to explore making its own health chips

Apple has a team exploring a custom processor that can make better sense of health information coming off sensors from deep inside its devices, job listings show.

The effort hints at Apple’s ability to pump out custom chips on as-needed basis, reflecting a greater level of vertical integration than other technology companies. Building custom chips for narrow functions can help Apple add new features and improve efficiency of its hardware while protecting its intellectual property from would-be imitatotrs.

A July 10 job posting from Apple’s Health Sensing hardware team says, “We are looking for sensor ASIC architects to help develop ASICs for new sensors and sensing systems for future Apple products. We have openings for analog as well as digital ASIC architects.”

2018-08-14 00:00:00 Read the full story.

 

Google reportedly developing speaker with screen to counter Amazon Echo Show

Google is aiming to challenge Amazon’s Echo Show by releasing its own smart speaker equipped with a screen in time for this year’s holiday season, Nikkei Asian Review reported today.

Nikkei Asian Review noted that the new product, based on Google’s Smart Display platform, would round out the Google Home lineup of smart speakers equipped with the voice-enabled Google Assistant artificial intelligence agent.
2018-08-17 20:31:30-07:00 Read the full story.

 

Google is now using AI to keep its data centers cool and save energy

Google is practicing what it preaches, handing control of one of the most vital components of its data center operation over to its machine-learning algorithms during the past few months.

DeepMind, the Google subsidiary that is responsible for much of its advanced artificial intelligence research, announced Friday that Google has saved 30 percent on its energy bills by improving the efficiency of its cooling systems. “This first-of-its-kind cloud-based control system is now safely delivering energy savings in multiple Google data centers,” Google said in a blog post.
2018-08-17 17:15:10-07:00 Read the full story.

 

Google Working On New ‘Coach’ AI Fitness Assistant For Wear OS

Artificial intelligence has always been something that Google has been integrating into a lot of its products. Now, it looks like the company is planning to bring it to Wear OS smartwatches, but this time it will be an AI coach that will assist users with their health and fitness goals.

Google Coach is being developed by Google under the codename Project Wooden, according to Android Police. The new AI assistant will be able to provide users with health and fitness data proactively. Google Coach will also be ale to deliver suggestions and recommendations for workouts and track the user’s progress. The assistant is also said to be capable of providing alternative workouts if a user was unable to fulfill a scheduled routine. Google Coach can log the user’s activity and it will use that data to provide suggestions in the future.

2018-08-16 04:51:33-04:00 Read the full story.

 

There’s a reason Siri, Alexa and AI are imagined as female – sexism

Virtual assistants are increasingly popular and present in our everyday lives: literally with Alexa, Cortana, Holly, and Siri, and fictionally in films Samantha (Her), Joi (Blade Runner 2049) and Marvel’s AIs, FRIDAY (Avengers: Infinity War), and Karen (Spider-Man: Homecoming). These names demonstrate the assumption that virtual assistants, from SatNav to Siri, will be voiced by a woman. This reinforces gender stereotypes, expectations, and assumptions about the future of artificial intelligence.

Fictional male voices do exist, of course, but today they are simply far less common. HAL-9000 is the most famous male-voiced Hollywood AI – a malevolent sentient computer released into the public imagination 50 years ago in Stanley Kubrick’s 2001: A Space Odyssey. Male AI used to be more common, specifically in stories where technology becomes evil or beyond our control (like Hal). Female AI on the other hand is, more often than not, envisaged in a submissive servile role.
2018-08-14 17:06:33+01:00 Read the full story.

 

Intel acquires Seattle-based deep learning startup Vertex.AI to bolster artificial intelligence efforts

Intel has acquired Vertex.AI, a three-year-old Seattle startup whose tools let developers add deep learning capabilities to their software.

Founded in 2015 by Choong Ng, Jeremy Bruestle, and Brian Retford, Vertex and its 7-person team will become part of the Movidius team within Intel’s Artificial Intelligence Products Group. Terms of the deal were not disclosed. “With this acquisition, Intel gained an experienced team and IP to further enable flexible deep learning at the edge,” Intel said in a statement.
2018-08-16 18:32:13-07:00 Read the full story.

 

Weekly Selection — Aug 17, 2018 – Towards Data Science

 

  1. The most important part of a data science project is writing a blog post
  2. Forecasting with Python and Tableau
  3. Better collaborative data science
  4. Don’t make this big machine learning mistake: research vs application
  5. Fine-tuning XGBoost in Python like a boss
  6. A Machine Learning Approach — Building a Hotel Recommendation Engine
  7. Creating custom Fortnite dances with webcam and Deep Learning
  8. Don’t Use Dropout in Convolutional Networks
  9. What App Descriptions Tell Us: Text Data Preprocessing in Python

2018-08-17 12:08:07.922000+00:00 Read the full story.

 


Behind Pay Walls/Registration Walls

Amazon’s secretive Cambridge Alexa start-up doubles revenue and headcount

A secretive Cambridge technology start-up acquired by Amazon that helped pioneer the Amazon Echo smart speaker has doubled its headcount and revenues.

Evi Technologies, which is owned by Amazon and was responsible for a significant part of the development of its Alexa artificial intelligence technology, doubled its revenues in 2017 to £36m, up from around £18m in 2016. The company also saw its staff numbers increase from 123 to 247 and increased its cash position from around £14m to £20.7m, according to its accounts.
2018-08-19 00:00:00 Read the full story.

 

Robots can easily sway children using peer pressure

Children can be easily swayed into changing their opinions by robots, according to new research which raises new questions over the ethics of artificial intelligence. In a series of tests by academics at the University of Plymouth, children aged between seven and nine were more likely to give the same responses as their robot companions, even when it was clear that suggestions made by the robots were wrong.

“What our results show is that adults do not conform to what the robots are saying. But when we did the experiment with children, they did,” said Tony Belpaeme, a Professor in Robotics at Plymouth. With children now having far more interaction with digital assistants such as Amazon’s Alexa…
2018-08-16 00:00:00 Read the full story.

 

M&S to replace call centre staff with AI that understands human speech

Marks & Spencer is replacing call centre staff with artificial intelligence designed to quickly deal with customer complaints. The company is using software from technology companies Twilio and Google to automate the routing of calls. Previously, people calling M&S would have to speak to a human operator to be transferred to the right department.

The new technology will be used in all 640 M&S UK stores by the end of September, as well as its 13 UK call centers. No jobs have been lost in the change, and the business will reassign over 100 employees to in-store roles, M&S said. M&S claims the technology correctly identifies 90pc of queries and can direct a call within seconds.
2018-08-15 00:00:00 Read the full story.

 


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