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Machine Futures

Trend Alert Admin 8 May 2019 Credibility


Machine learning will be the biggest and fastest-growing trend in technology again in 2019, threatening every laggard organization and offering rich prizes for the leaders, big and small. Read to discover what our robot, Athena, has found on the future of machines and act accordingly, or click any link to read the evidence she found in 3,270 reports, articles and presentations from around the web.
What is changing?

If you are new to foresight, we recommend you view this slide presentation first.

Quick Summary

The new summary visuals below are completely machine produced, showing our robot's global analysis of:

Driving Forces (Beta)

Causations (Beta)

Who and what are causing these changes:



Potential solutions

What are others doing to seize opportunities or minimise risks?



You can learn more, click through to more detail on 'machine' futures and run collaborative, digital  workshops on these findings at /home.

More analysis
This summary analysis draws from our robot's below visualizations of the future of machines and draws from different vantage points to tell the story of what's emerging just like a GPS system.


Cloud: The range of opportunity for machine learning (ML) and improvement is enormous with many incumbents and start-ups finding new ways to increase machines' efficiency, effectiveness, predict time-to-failure and gather new intelligence about performance and customer usage. ML will permeate everyone's lives in the years to come.Systems map: The systems map clearly shows that the next five years are expected to deliver tremendous advances in artificial intelligence, algorithms, robots, use of big data, software agents and the IoT.

Radar chart: On the radar are the use of ML in the vehicles, railways, food, digital money, manufacturing and data analysis and far greater prediction and automatic decision-making replacing many human rote jobs but creating many new ones too.

Graph-It: By 2025, ML will be advancing fast in healthcare and employing the IoT far beyond anything we imagine today.

Spline chart: The two Spline Charts we have provided this week show just how ML has exploded on to the scene in the last three years. From a background, specialism, ML is now expected to be a megatrend for the next ten years and possibly beyond.

Year-on-Year: Interest in improving the use of machines can again be seen in how sectors are now waking up to both the threat and the opportunity. In 2017, interest was medium with automotive, IT and Financial Services leading the charge but last year this moved up to high with most sectors now looking to gain advantage. Only the water sector is a singleton at the back of the pack. 2019 shows the same early pattern with interest now very high in all sectors except water.

Sentiment: Positive sentiments far outweigh negative feelings with the potential for huge future innovation and earnings driving the sectors' interest. But concerns are also being voice about the risk of increased cyberattacks and potential disruptions to travel, payments and stealing, or misuse of, customer data.

Pie Charts: The growing increase in machine learning is tempered by the fact that we are perhaps a generation away from reaching a tipping point in the public's acceptance of these changes as the new normal. And, this is also reflected in that 61.0% of initiatives are still in early stage. However, enough traction has already been achieved for the markets to believe that opportunities abound for making additional billions and even trillions from machines.

Heat map: The Heat Map shows the current patchiness of efforts however, with China, the US and the UK leading ML developments and IT the prime sector focus right now for most countries. We expect the Heat Map to become far more populated and with far more High spots as the next decade unfolds. The cross-impact chart also indicates just how many gaps there are for entrepreneurs to exploit right now before others gain a dominant hold.

Emergent drivers: Right now, the emerging drivers chart below shows machines as in the Differentiating Wave – a wave that offers high differentiation from slower players.

Geography: Geographically, the top countries for machine exploitation and future significant earnings are China, the U.S., India, Ireland, Canada, Australia and South Korea.

Others will have to move fast to overhaul them.

SWOT: Lastly, the SWOT chart shows many opportunities for machine futures with relatively few weaknesses and threats too. Time to plunge in before it's too late!

 Visuals

For more detailed explanation of the graphics below please click here. All outlooks based on 2025 unless otherwise stated.

Cloud
The range of opportunity for machine learning (ML) and improvement is enormous with many incumbents and start-ups finding new ways to increase machines' efficiency, effectiveness, predict time-to-failure and gather new intelligence about performance and customer usage. ML will permeate everyone's lives in the years to come.

System map
The systems map clearly shows that the next five years are expected to deliver tremendous advances in artificial intelligence, algorithms, robots, use of big data, software agents and the IoT.


Radar chart
On the radar are the use of ML in the vehicles, railways, food, digital money, manufacturing and data analysis and far greater prediction and automatic decision-making replacing many human rote jobs but creating many new ones too.



Graph-It
By 2025, ML will be advancing fast in healthcare and employing the IoT far beyond anything we imagine today.

Spline
The two Spline Charts we have provided this week show just how ML has exploded on to the scene in the last three years. From a background, specialism, ML is now expected to be a megatrend for the next ten years and possibly beyond.

Trend Wave - Today

Trend Wave – 3 years ago

 

Year-On-Year

Interest in improving the use of machines can again be seen in how sectors are now waking up to both the threat and the opportunity. In 2017, interest was medium with automotive, IT and Financial Services leading the charge but last year this moved up to high with most sectors now looking to gain advantage. Only the water sector is a singleton at the back of the pack.

2019 shows the same early pattern with interest now very high in all sectors except water.

Sentiment

Positive sentiments far outweigh negative feelings with the potential for huge future innovation and earnings driving the sectors' interest. But concerns are also being voice about the risk of increased cyberattacks and potential disruptions to travel, payments and stealing, or misuse of, customer data.


Pie Charts
The growing increase in machine learning is tempered by the fact that we are perhaps a generation away from reaching a tipping point in the public's acceptance of these changes as the new normal. And, this is also reflected in that 61.0% of initiatives are still in early stage. However, enough traction has already been achieved for the markets to believe that opportunities abound for making additional billions and even trillions from machines.



Heat map

The Heat Map shows the current patchiness of efforts however, with China, the US and the UK leading ML developments and IT the prime sector focus right now for most countries. We expect the Heat Map to become far more populated and with far more High spots as the next decade unfolds.

The cross-impact chart also indicates just how many gaps there are for entrepreneurs to exploit right now before others gain a dominant hold.

 

Emergent drivers

Right now, the emerging drivers chart below shows machines as in the Differentiating Wave – a wave that offers high differentiation from slower players.


Geography

Geographically, the top countries for machine exploitation and future significant earnings are China, the U.S., India, Ireland, Canada, Australia and South Korea.

Others will have to move fast to overhaul them.

 

SWOT

Lastly, the SWOT chart shows many opportunities for machine futures with relatively few weaknesses and threats too. Time to plunge in before it's too late!




Evidence

Search term: “wearable*”. Use this search term to explore our database for more knowledge and wisdom and latest data and information on the topic.

Implications

algorithm

  • learning
  • market
  • intelligence
  • capability
  • platform
  • technology
  • rate
  • machine
  • machine vision sale
  • processing
  •  

    Potential Responses

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    Sources
    Athena used the sources below as the top ones to create this report and determined which embedded forecasts are included in this Trend Alert. She found 3,270 forecasts in seconds on 8th May 2019 to allow us to publish this report in less than two hours. She can turn these into PowerPoint slides and Audio files in minutes too as you wish, or we can prepare a full customized and professionally written brief for you to order covering all these forecasts.

    Athena
    Athena does show duplicates to aid your understanding of themes as well as contradictory forecasts. She may also show near-duplicates. You can speed read past the duplicates and near-duplicates if you wish, though the latter may show additional information. You can use the contradictory, and likely uncertain forecasts she finds to imagine different scenarios. The future is unpredictable, but we can examine the possibilities and choose our preferable future from the choices she presents. 

    Athena is apolitical. She will report forecasts from different viewpoints however distasteful that might be to our own values. Wearing rose-colored glasses is not her purpose; reporting potential futures is. So, we recommend you check her veracity before responding to her extracted forecasts.

    Just like humans, Athena can be fallible. Do recognize that you and your associates are biased too. But whereas you tire, make mistakes and only recognize what interests you, she does not. She might miss or misinterpret as you do, but with far less frequency and she'll take uncomfortable truths and alternative ideas in her stride. But, please let us know if you feel her bias can be reduced. We want to do our best for you. And, as with any research, you should check and triangulate her findings for yourself.

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