Jeffrey Phillips

APRIL 8, 2019

But through this I've learned a bit about both innovation and digital transformation. Below I'm going to share a few things I've learned so far, and my sense of the implications. Learnings so far: Innovation and digital transformation both impact efficiency; only innovation is about creating dramatically new stuff (so far).

Artificial Inteligence 179

Artificial Inteligence Learning Technical Review Big Data 179

Paul Hobcraft

APRIL 1, 2018

We are learning to connect in completely different ways. We are learning how to interact with a connected system as products move into products and digital, connected and combined. So are you learning a new innovation language? As we gain understanding we are getting more fluid, we learn and adjust to constantly improve.

Learning 190

Learning Design Innovation Technology 190

Corporate Innovation

JANUARY 25, 2016

In this two-part series, we will discuss the big data challenge facing the automotive industry. The pieces are the result of my work in the industry helping corporations with their innovation and big data strategies. There is much less conversation about the fifth dimension.

Big Data 58

Big Data Data System Artificial Inteligence 58

Corporate Innovation

JANUARY 25, 2016

In this two-part series, we will discuss the big data challenge facing the automotive industry. The pieces are the result of my work in the industry helping corporations with their innovation and big data strategies. There is much less conversation about the fifth dimension.

Big Data 58

Big Data Data System Artificial Inteligence 58

mjvinnovation

MAY 24, 2019

In this context, Big Data provides important data about customer behavior. Big Data refers to data that grows unstructured and exponentially in the world and is driven by three factors: volume, variety and data rate. ” Guide the management and implementation of Big Data.

Big Data 40

Big Data Data Survey Technical Review 40

ITONICS

JUNE 3, 2019

How machine learning is revolutionizing the search for trends and technologies. This paper presents the results of a study on the challenges to successful innovation management in companies and introduces an environmental scanning system that increases the efficiency of innovation management using big data analytics.

Big Data 28

Big Data Innovation Management Data Artificial Inteligence 28

ITONICS

JUNE 3, 2019

How machine learning is revolutionizing the search for trends and technologies. This paper presents the results of a study on the challenges to successful innovation management in companies and introduces an environmental scanning system that increases the efficiency of innovation management using big data analytics.

Big Data 28

Big Data Innovation Management Data Artificial Inteligence 28

IdeaConnection

MARCH 8, 2019

A farming app and machine learning models to predict the performance of seed varieties.

Artificial Inteligence 49

Artificial Inteligence Big Data Learning Data 49

Corporate Innovation

JANUARY 25, 2016

In this two-part series, we will discuss the big data challenge facing the automotive industry. The pieces are the result of my work in the industry helping corporations with their innovation and big data strategies. There is much less conversation about the fifth dimension.

Big Data 40

Big Data Data System Artificial Inteligence 40

IdeaConnection

AUGUST 13, 2018

Using big data, prediction modeling and machine learning to detect fraudulent insurance claims.

Big Data 40

Big Data Data Artificial Inteligence Learning 40

Corporate Innovation

JANUARY 3, 2017

As I argue in my new book The Big Data Opportunity in Our Driverless Future , the key differentiators will be the personalized transportation experiences that can be offered by properly combining these technologies and services with insights derived from the continuous exploitation of big data collected from inside and outside the vehicle.

Big Data 40

Big Data Data Industry Technology 40

Corporate Innovation

JANUARY 3, 2017

As I argue in my new book The Big Data Opportunity in Our Driverless Future , the key differentiators will be the personalized transportation experiences that can be offered by properly combining these technologies and services with insights derived from the continuous exploitation of big data collected from inside and outside the vehicle.

Big Data 40

Big Data Data Industry Technology 40

Corporate Innovation

JANUARY 3, 2017

As I argue in my new book The Big Data Opportunity in Our Driverless Future , the key differentiators will be the personalized transportation experiences that can be offered by properly combining these technologies and services with insights derived from the continuous exploitation of big data collected from inside and outside the vehicle.

Big Data 40

Big Data Data Industry Technology 40

etventure

DECEMBER 7, 2018

At the Data Natives Conference in Berlin for three days it was all about data, technologies and innovation: 4 stages, more than 100 speakers and around 1,600 visitors. In his speech “Big Data is dead” he explained how companies can generate real added value from their data. 5 Facts on Data Thinking.

Big Data 40

Big Data Data Conference Artificial Inteligence 40

Destination Innovation

DECEMBER 13, 2019

Now big data and artifical intelligence (AI) have changed the playing field. There are now software products which can scour diverse data to find promising starting points for your innovation goals. They aim to use machine learning to find diverse signals from huge sources and separate them from the noise.

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Artificial Inteligence Big Data Innovation Data 246

Acuvate

MAY 22, 2020

10 Key Challenges Data Scientists Face in Machine Learning projects AI-driven, powered by AI, transforming with AI/ML, etc., Everyone is chasing after the promised land of machine learning but so few fully understand it. The post Key Challenges Data Scientists Face in Machine Learning projects appeared first on Acuvate.

Artificial Inteligence 95

Artificial Inteligence Data Project Learning 95

Paul Hobcraft

OCTOBER 2, 2023

This shift has prompted innovation to develop tools and design approaches that support these changes in several critical ways based on four global aspects: Learning from real-time data : Traditional analytics models and past performance data may not be entirely relevant in today’s ever-changing business landscape.

Design Thinking 148

Design Thinking Technical Review Design Technology 148

IdeaScale

JANUARY 3, 2019

Everybody talks about big data, but fintech has an advantage in that it’s been working with data for decades. Creative approaches to data are going to be particularly important, and innovation strategy will be key. Asking employees what they see in the data can lead to new approaches and ideas. Transparency.

Trends 113

Trends Big Data Crowdsourcing Data 113

Acuvate

MARCH 16, 2019

Data Analytics in Business. According to Stastia , the global big data market is forecasted to grow to 103 billion U.S. If you are an organization set out to embrace data analytics, here’s a list of the top 5 myths you need to be aware of. Myth 1: Only large companies with big data need data analytics.

Data 80

Data Artificial Inteligence Technical Review Big Data 80

mjvinnovation

APRIL 26, 2019

In our Data Science universe, it represents Machine Learning. Machine learning is nothing more than a model of data analysis. The method starts from the premise that the machine can learn from the data collected, that is, it is able to identify patterns and make decisions on its own, with little human intervention.

Artificial Inteligence 40

Artificial Inteligence Learning Data Analysis 40

Acuvate

APRIL 12, 2023

With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity. Combined with machine learning and advanced analytics, AI allows smart factories to evaluate data, forecast outcomes and failures, control downtimes and maximize output.

Data 52

Data Artificial Inteligence Technical Review Big Data 52

Acuvate

APRIL 12, 2023

With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity. Combined with machine learning and advanced analytics, AI allows smart factories to evaluate data, forecast outcomes and failures, control downtimes and maximize output.

Data 52

Data Artificial Inteligence Technical Review Big Data 52

Acuvate

JANUARY 29, 2019

Companies like Danone leveraged machine learning enabled trade promotion forecasting tools and witnessed a reduction of 30% in lost sales. Machine learning offers the added boost to enhance the accuracy of forecasting. An additional benefit that machine learning offers is it improves the forecasting ability of these tools over time.

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Artificial Inteligence Big Data Data Software Review 92

IdeaConnection

JUNE 11, 2018

A big data and artificial intelligence software model predicts whether hospitalized patients will survive, better than traditional models.

Artificial Inteligence 40

Artificial Inteligence Big Data Learning Software 40

etventure

AUGUST 4, 2020

Deep Learning) require access to huge amounts of data to reach their full potential. Many countries globally have recognized that the handling and processing of these large data sets depend heavily on the agile innovation engines of our economies – the startups.

Data 52

Data Big Data Artificial Inteligence Technical Review 52

Paul Hobcraft

MAY 9, 2023

I think of the Gartner Hype Cycle here as we have gone through each of the stages of recognition of the application and the learning from this; we have the innovation triggers first, then a peak or inflated expectations, followed by troughs of disillusionment and finally by the slope of enlightenment, to give a new plateau of productivity.

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Artificial Inteligence Technical Review Agile Innovation 183

Acuvate

DECEMBER 7, 2022

Industrial IIoT, in particular, in the form of sensors, flow meters, and edge devices, are being used to collect on-field data to create situational awareness and identify leaks, sewer overflows, and faulty equipment before these require costly repairs. How are sustainable technological solutions enabling Smart Water Management (SWM)?

Data 78

Data Artificial Inteligence Management Technical Review 78

IdeaScale

FEBRUARY 19, 2020

Learn how to get those creative juices flowing with tools such as: Google Docs Visual Thesaurus Coggle and more. Learn four ways to rock your next brainstorming session in this post. Learn more about with sustainable innovation is and how you can create sustainability with your innovation strategies in this article.

Brainstorming 173

Brainstorming Crowdsourcing Conference Product Development 173

Acuvate

OCTOBER 10, 2022

Darryl Williams, Corporate Vice President of Energy at Microsoft , rightly said, “Technologies like AI and machine learning can analyze the past, optimize the present, and predict the future.” This data repository is analyzed by AI algorithms in real time. AI Applications in the Oil and Gas Industry. Driving workplace safety.

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Artificial Inteligence Industry Big Data Data 66

IdeaScale

OCTOBER 31, 2018

But what can you learn from a large-scale crowdsourced research program like All of Us? In the future, big data will lead to highly relevant insights into how each choice we make, each environment we encounter, each part of our genetic make-up will lead to complex consequences and outputs in us. Well, tons, really.

Big Data 113

Big Data Crowdsourcing Data Trends 113

Acuvate

NOVEMBER 6, 2019

Azure Synapse, built on Azure SQL Data warehouse, is an evolved analytics service, intended to bridge the gap between data warehouses and data lakes. It offers a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning applications. Data Engineers, data.

Data 49

Data Artificial Inteligence Big Data Learning 49

Acuvate

NOVEMBER 28, 2019

Using Big Data and Advanced Analytics. Retailers and CPG companies capture torrential amounts of data from transactions and also have access to a wide array of information from the media. Big Data and advanced analytics opens the floodgates of opportunities for CPG companies to use data to their benefit.

Trends 72

Trends Industry Big Data Technical Review 72

Idea to Value

JULY 1, 2020

There are assessments for nearly everything and big data will probably provide more on the less tangible things like creativity and likeability. However the criteria for advancement must give a lot of weight to creativity, collaboration and the capacity to learn and change.

Report 148

Report Big Data Leadership LEAN 148

Idea to Value

MARCH 11, 2016

The big upcoming leaps come from research into how machines can emulate the human thought process. In recent years, big data and deep learning algorithms, and the ability to spread processing power across thousands of computers in the cloud, is making this process more and more effective. Machine Learning.

Creativity 100

Creativity Big Data Data Technical Review 100

Ecosystems4Innovating

NOVEMBER 2, 2023

Machine Learning and AI-Driven Insights : Integrating AI and machine learning into the Design Thinking process can provide valuable insights. For example, AI can analyze large datasets of user feedback to identify patterns and trends, guiding designers in making data-informed decisions.

Design Thinking 59

Design Thinking Design Technical Review Artificial Inteligence 59

Acuvate

JANUARY 2, 2020

Advanced analytics helps to mine through big data for actionable insights which can be used for a plethora of business use cases. The company predicted the probability of drivers having incidents by integrating telematics and tachograph infringement data with weather data and harnessing the data set with machine learning.

Industry 59

Industry Artificial Inteligence Big Data Data 59

Yet2

JANUARY 9, 2023

Using Big Data in our own scouting activities has been an investment we’ve been making over the few years. To help make this intangible concept feel a little more real, below we share just 3 examples of how we at yet2 leverage Big Data in our scouting: Starting with unique, quality datasets: avoid “garbage in, garbage out.”

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Big Data Open Innovation Data Underperforming Technical Team 52