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Category: business – Page 256

10 Charts That Will Change Your Perspective On Artificial Intelligence’s Growth

  • There has been a 14X increase in the number of active AI startups since 2000. Crunchbase, VentureSource, and Sand Hill Econometrics were also used for completing this analysis with AI startups in Crunchbase cross-referenced to venture-backed companies in the VentureSource database. Any venture-backed companies from the Crunchbase list that were identified in the VentureSource database were included.

  • The share of jobs requiring AI skills has grown 4.5X since 2013., The growth of the share of US jobs requiring AI skills on the Indeed.com platform was calculated by first identifying AI-related jobs using titles and keywords in descriptions. Job growth is a calculated as a multiple of the share of jobs on the Indeed platform that required AI skills in the U.S. starting in January 2013. The study also calculated the growth of the share of jobs requiring AI skills on the Indeed.com platform, by country. Despite the rapid growth of the Canada and UK. AI job markets, Indeed.com reports they are respectively still 5% and 27% of the absolute size of the US AI job market.

  • Machine Learning, Deep Learning and Natural Language Processing (NLP) are the three most in-demand skills on Monster.com. Just two years ago NLP had been predicted to be the most in-demand skill for application developers creating new AI apps. In addition to skills creating AI apps, machine learning techniques, Python, Java, C++, experience with open source development environments, Spark, MATLAB, and Hadoop are the most in-demand skills. Based on an analysis of Monster.com entries as of today, the median salary is $127,000 in the U.S. for Data Scientists, Senior Data Scientists, Artificial Intelligence Consultants and Machine Learning Managers.

  • Error rates for image labeling have fallen from 28.5% to below 2.5% since 2010. AI’s inflection point for Object Detection task of the Large Scale Visual Recognition Challenge (LSVRC) Competition occurred in 2014. On this specific test, AI is now more accurate than human These findings are from the competition data from the leaderboards for each LSVRC competition hosted on the ImageNet website.

  • Global revenues from AI for enterprise applications is projected to grow from $1.62B in 2018 to $31.2B in 2025 attaining a 52.59% CAGR in the forecast period. Image recognition and tagging, patient data processing, localization and mapping, predictive maintenance, use of algorithms and machine learning to predict and thwart security threats, intelligent recruitment, and HR systems are a few of the many enterprise application use cases predicted to fuel the projected rapid growth of AI in the enterprise. Source: Statista.

  • 84% of enterprises believe investing in AI will lead to greater competitive advantages. 75% believe that AI will open up new businesses while also providing competitors new ways to gain access to their markets. 63% believe the pressure to reduce costs will require the use of AI. Source: Statista.

  • 87% of current AI adopters said they were using or considering using AI for sales forecasting and for improving e-mail marketing. 61% of all respondents said that they currently used or were planning to use AI for sales forecasting. The following graphic compares adoption rates of current AI adopters versus all respondents. Source: Statista.

5 biggest risks of sharing your DNA with consumer genetic-testing companies

Some individuals worry they will discover things about their DNA that will be frightening — namely, the risks they run of contracting various diseases — and not know how to move forward with the information. Professional scientific skeptics contend the information may not even be as accurate as claimed, and lead people to make questionable health decisions. But there’s another type of risk that consumers aren’t focusing on as much, and it’s a big one: privacy. There is nothing more private than your personal genetic information, and sending away for a personal genome kit means sharing your DNA with the testing companies. What do they do with it, beyond providing consumers with genetic and health assessments?

Consumer DNA genetic testing kits are a booming business, and the biggest risk isn’t necessarily uncovering a health scare; it’s what these companies may do, or be forced to do, with your genetic data.

New (?) ideas for utilizing space for business: hypergravity for isotopic enrichment

One night, as I was putting my daughter to bed and waiting for her to fall asleep, I tried to think of some new markets for space utilization.

We often hear about attempts to find industrial uses for microgravity for growing crystals, for purification of electronic materials (which is an actual thing with ACME Advanced Materials: http://www.a2-m.com/), maybe growth of certain metal foams, etc. However, in space, you’re in both a hard vacuum and not physically resting on anything, so you can spin up something, and it will simply keep on spinning (stably, if you spin it around the correct axis) nearly indefinitely without any additional energy input and no wear on bearings or anything. So in fact, you can get basically any gravity level you want, including HYPERgravity, nearly for free.

What are the applications of this?

The Brilliant Ways UPS Uses Artificial Intelligence, Machine Learning And Big Data

Autonomous deliveries and drones

UPS execs insist that the UPS driver is a core element to its success and the face of the company, but they have tested the use of drone deliveries for some applications including dropping essential supplies in Rwanda and demonstrating how medicine could be delivered to islands. In rural areas, where drones have open air to execute deliveries and the distance between stops makes it challenging for the drivers to be efficient, drones launched from the roofs of UPS trucks offer a solid solution to cut costs and improve service. Drones could also be deployed in UPS sorting facilities and warehouses to get items on high shelves or in remote areas.

The technology used by UPS generates a cache of data that opens up even more opportunities to become more efficient, improve the customer experience, innovate delivery solutions, and more. From optimizing the UPS network to driving operational improvements, big data and artificial intelligence are at the core of UPS’s business performance.

How microgrids could boost resilience in New Orleans

During Hurricane Katrina and other severe storms that have hit New Orleans, power outages, flooding and wind damage combined to cut off people from clean drinking water, food, medical care, shelter, prescriptions and other vital services.

In a year-long project, researchers at Sandia and Los Alamos national laboratories teamed up with the City of New Orleans to analyze ways to increase community resilience and improve the availability of critical lifeline services during and after severe weather.

The team used historical hurricane scenarios to model how storms cause localized flooding, disrupt the electrical system and cut off parts of the community from lifeline services. Sandia researchers then developed a tool to analyze and identify existing clusters of businesses and community resources in areas less prone to inundation—such as gas stations, grocery stores and pharmacies that could be outfitted with microgrids to boost resilience.

Juvenescence Completes $50 Million Series A Financing Round

We were interested to learn that Juvenescence Limited, a biotech and development company involved in the development of therapies that target the aging processes, has successfully raised $50 million in a series A financing round.

Jim Mellon, the chairman of Juvenescence Limited, said, “We are delighted with the progress we have made and the faith that investors have placed in us to build a world-class company, one that we hope will lead the field in longevity science for the benefit of humanity as well as yield superb returns for our shareholders. Our company ethos is to advance the science that will add years of healthy life to every human being, and that is exactly what we are executing on at record speed.”

Juvenescence has raised $63 million from various international investors since its creation in October 2016 and is now moving forward with a number of key projects. The company is comprised of a number of industry leaders in business as well as a solid scientific team led by Dr. Declan Doogan and Dr. Annalisa Jenkins.

Why fascism is so tempting — and how your data could power it

In a profound talk about technology and power, author and historian Yuval Noah Harari explains the important difference between fascism and nationalism — and what the consolidation of our data means for the future of democracy. Appearing as a hologram live from Tel Aviv, Harari warns that the greatest danger that now faces liberal democracy is that the revolution in information technology will make dictatorships more efficient and capable of control. “The enemies of liberal democracy hack our feelings of fear and hate and vanity, and then use these feelings to polarize and destroy,” Harari says. “It is the responsibility of all of us to get to know our weaknesses and make sure they don’t become weapons.” (Followed by a brief conversation with TED curator Chris Anderson)

Check out more TED Talks: http://www.ted.com

The TED Talks channel features the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design — plus science, business, global issues, the arts and more.

Follow TED on Twitter: http://www.twitter.com/TEDTalks
Like TED on Facebook: https://www.facebook.com/TED

Technical Analysis: Can it predict future asset value?

I love clearing the air with a single dismissive answer to a seemingly complex question. Short, dismissive retorts are definitive, but arrogant. It reminds readers that I am sometimes a smart a*ss.

Is technical analysis a reasoned approach for
investors to predict future value of an asset?

In a word, the answer is “Hell No!”. (Actually, that’s two words. Feel free to drop the adjective). Although many technical analysts earnestly believe their craft, the approach has no value and does not hold up to a fundamental (aka: facts-based) approach.

One word arrogance comes with an obligation to substantiate—and, so, let’s begin with examples of each approach.

Investment advisors often classify their approach to studying an equity, instrument or market as either a fundamental or technical. For example…

  • Fundamental research of a corporate stock entails the analysis of the founders’ backgrounds, competitors, market analysis, regulatory environment, product potential and risks, patents (age and legal challenges), track record, and long term trends affecting supply and demand.A fundamental analysis may study the current share price, but only to ascertain the price-to-earnings ratio compared to long term prospects. That is, has the market bid the stock up to a price that lacks a basis for long term returns?
    .
  • On the other hand, a technical approach tries to divine trends from recent performance—typically charting statistics and pointing to various graph traits such as resistance, double shoulders, and number of reversals. The approach is more concerned with assumptions and expectations of investor behavior—or hypotheses and superstition related to numerology—than it is with customers, products, facts and market demand.

Do you see the difference? Fundamental analysis is rooted in SWOT: Study strengths, weaknesses, opportunities, and threats. Technical analysis dismisses all of that. If technical jargon and approach sound a bit like a Gypsy fortune teller, that’s because it is exactly that! It is not rooted in revenue and market realities. Even if an analyst or advisor is earnest, the approach is complete hokum.

I have researched, invested, consulted and been an economic columnist for years. I have also made my mark in the blockchain space. But until now, I have hesitated to call out technical charts and advisors for what they are…

Have you noticed that analysts who produce technical charts make their income by working for someone? Why don’t they make a living from their incredible ability to recognize patterns and extrapolate trends? This rhetorical question has a startlingly simple answer: Every random walk appears to have patterns. The wiring of our brain guarantees that anyone can find patterns in historical data. But the constant analysis of patterns by countless investors guarantees that the next pattern will be unrelated to the last ones. That’s why short term movement is called a “random walk”. Behaviorists and neuroscientists recognize that apparent relationships of past trends can only be correlated to future patterns in the context of historical analysis (i.e. after it has occurred).

Decisions based on a technical analysis—instead of solid research into fundamentals—is the sign of an inexperienced or gullible investor. Some advisors who cite technical charts know this. Technicals have no correlation to long term appreciation, asset quality or risks. They only point to short term possibilities.

The problem with focusing on short-term movement is that you will certainly lose to insiders, lightning-fast program traders, built in arbitrage mechanisms and every unexpected good news/bad news bulletin.

If you seek to build a profit in the long run, then do your research up front, enter gradually, and hold for the long term. Of course, you should periodically reevaluate your positions and react to significant news events from trusted sources. But you should not anguish over your portfolio every day or even every month.

  • Know your objectives
  • Set realistic targets
  • Research by reading contrarians and skeptics (They help you to avoid confirmation bias)
  • Study comparables and reason through the likelihood that another technology or instrument poses a threat to the asset that interests you
  • Then, invest only what you can afford to lose and don’t second guess yourself frequently
  • Dollar-cost-average
  • Revaluate semi-annually or when meeting with direct sources of solid, fundamental information

Finally, if someone tries to dazzle you with charts of recent performance and talk of a “resistance level” or support trends, smile and nod in approval—but don’t dare fall for the Ouija board. Send them to me. I will straighten them out.

Who says so? Does the author have credentials?

I originally wrote this article for another publication. Readers challenged my credentials by pointing out that I am not a academic economist, investment broker or financial advisor. That’s true…

I am not an academic economist, but I have certainly been recognized as a practical economist. Beyond investor, and business columnist, I have been keynote speaker at global economic summits. I am on the New Money Systems Board at Lifeboat Foundation, and my career is centered around research and public presentations about money supply, government policy and blockchain based currencies. I have advised members of president Obama’s council of economic advisors and I have recently been named Top Writer in Economics by Quora.

Does all of this qualify me to make dismissive conclusions about technical analysis? That’s up to you! This Lifeboat article is an opinion. My opinion is dressed as authoritative fact, because I have been around this block many times. I know the score.

Related:

Philip Raymond co-chairs CRYPSA, hosts the Bitcoin Event and is keynote speaker at Cryptocurrency Conferences. He sits on the Lifeboat New Money Systems board. Book a presentation or consulting engagement.

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