Monday, December 19, 2016

Kobielus thought leadership in all things data in 2016

Predictions for Deep Learning in 2017

How We Will Harvest Cognition in 2017

Maximizing the value of high-performance statistical analysis and reporting

Gauging your organization’s readiness to drive digital disruption

Big Data: Main Developments in 2016 and Key Trends in 2017

Kobielus Predictions for Data Science in 2017

Big data and analytics trends in 2017: James Kobielus’s predictions

How cognitive computing will touch your life in 2017

How the backlash against cognitive computing will play out in 2017

Data industry experts offer 2017 predictions throughout December

Tackling predictive uncertainty with Monte Carlo statistical analysis

The Experience of Being a High-Performing Data Scientist

Moving beyond spreadsheets into enterprise-ready statistical analysis

Data science expert interview: Dez Blanchfield, Craig Brown, David Mathison, Jennifer Shin and Mike Tamir

The Controversy over Algorithmic Newscycle Curation

Accessing the power of R through a robust statistical analysis tool

Coming to Grips with Artificial Intelligence’s Many Manifestations

Deep learning is already altering your reality

Embodying Every Last Thing With Cognition

Accelerating deep learning to superhuman proportions

Making a better world with cognitive systems: Wrapping up World of Watson

The cognition blitz at World of Watson 2016

A deeper shade of simplicity at IBM Insight at World of Watson 2016

Disrupting business with team data science at IBM Insight at World of Watson 2016

Keeping a clear mind about the potential downsides of AI

Center your business strategy on predictive analytics at IBM Insight at World of Watson 2016

Enabling chief data officer success at IBM Insight at World of Watson 2016

Building a cognitive business at IBM Insight at World of Watson 2016

Putting data to work at Strata + Hadoop World 2016

5 reasons data engineers are attending IBM Insight at World of Watson

Fresh Blood: The Democratization of Enterprise Data Science

Driving Data Science Productivity Without Compromising Quality

Instilling Industrial Discipline in Enterprise Analytics

Next-generation data science: Open analytics ecosystems

Data science expert interview: Influencer roundtable

Next-generation data science: Acceleration for team productivity

Data science predicts election winner!

Doing the Data Science That Drives Predictive Personalization

Collaborate to foster cognitive disruption

The Acceleration of Data Science Excellence

Getting the right mix of analytics specialists in data science teams

Know when your big data is telling big lies

Grappling with first-world problems and data-fueled disruptions

The Social Analytics of What Passes for Political Conversation These Days

Using Cognitive Computing to Prevent Human Cognitive Decline

Doing the Data Science That Drives Extreme Personalization

Federating Unfettered Analytics Across IoT’s Sprawl

Surmounting huge hurdles to algorithmic accountability

Big Brother, Crowd Control, and Pokémon Go

The Emotional Arc of Data Storytelling

Cognitive Chatbots in the Patterns of Our Lives

Encroaching Commoditization in Data Science

Pushing Data-Science Automation To Its Practical Limits

Drilling and Building: The Power Apps of Machine Learning
Accentuating the positive vision of cognitive computing’s potential

Big Data Tells Many Stories, Some of Them Spurious

Advancing the art of the cognitive chatbot

Deep Learning and the Deep Warping of the Photographic Record

Making Your Data Progressively Smarter

Eliciting high-quality data science from non-traditional sources

Highlights from the Apache Spark Maker Community Event

The Rise of Open Data Science. Join Us June 6th

Open Data Science Innovation in the Cloud

What is Business Intelligence?

Don’t Fence Me In: Tensions on the Data Science Frontier

Bridging to a hybrid cloud data services architecture

Vetting the Actual Science Behind Data Science

How to monetize the fuzzy narratives of social listening

Giving citizen data scientists a short leash

Distributing Machine Intelligence to the Foggy Edge of the IoT

On Big Data and Data Science. Interview with James Kobielus

3 safeguards for intelligent machines

Merrymaking vs. Mischief: Beating Machine-Learning Algorithms At Their Own Game 

Precipitating money from the edges of the Internet of Things

Algorithmically Detecting Cyberattack Patterns in the Absence of Open Training Data

Pattern Curators of the Cognitive Era

Using Machine Learning to Ward Off Zero-Day Attacks on the Internet of Things

Allaying Anxieties Surrounding the Potential of Artificial Intelligence
Can We Use Social Listening as a Virtual Breathalyzer?

Communications Connection: Is big data still relevant?

Real Time Isn’t As Real As You’ve Been Led to Believe

Mining and Divining The Mysteries Of The Mind

Open Source Analytics Penetrating Deeper into the Internet of Things

Surprise in the Narrative Flow of Data Science

How Cognitive Computing Can Boost Educational Performance

From Creation to Gustation: How Modern Foodchains Crave Precision Analytics

The Bubble Edens of IoT Mood Management

The Sitting-Duck Machine-Learning Model

A More Brilliant Fog: Containerizing Algorithmic Services at the IoT’s Edges

Interview with James Kobielus, Big Data Evangelist, IBM

The Anti-Bias Bias of the Data Scientist

Empathetic vs. Pathetic: Living With Affective Computing

Graph analysis: Not the dots, but the connections

Survival of Fitness: How Model Selection Happens In The Natural Order of Data Science

Morphing Targets and Fancy Math

The Merry Melodious Milling of Machine-Learning Music

Statistically Slicing Through the Knotty Tangle of Human Morality

The Evenly Matched Global AI Arms Race

The robotic throttling of information overload

Emotion Analytics and the Algorithmic Parsing of the C-Suite Poker Face

Statistically Crunching a Crowdsourced Image of the World in Flux

Paths, Patterns, and Lakes: The Shapes of Data to Come

Cognitive Coaching: The Algorithmic Acceleration of Human Learning

Quarks: Embedding Open Cognitive Analytics at the Edge of the Internet of Things

Deploying analytics microservices in the cloud

Optimizing the Physical Fitness of The Community At Large

Becoming cognitive: a new disruptor remakes the business landscape

Dredging the Data Lake Down to Its Muddy Bottom

What’s the Threshold at Which Big Data May Be Considered Mainstream?

Crowdsourcing Verbal Context for Deep Visual Analysis

Controlling the Weaponization of Deep Learning

Pondering The Prophesied Master Learning Algorithm

Machine learning models need love, too

The Rashomon Effect in Algorithmic IoT Memory Capture

The Deeply Embedded Future of Deep Learning

You Wouldn’t Know Humor If It Bit You in the Algorithm!

Digital Placebo: The Psychosomatic Impacts of Quantified Self

The Internet of Things will eliminate data deadzones

Citizen Data Scientists in the New Global Order

The Bottomless Log of Everything

The Remorseless Recrystallization of the Open Source Analytics Ecosystem

Fitting Data Science Methodologies to the Complex Contours of the Internet of Things

2020 vision: The triumph of cognitive IoT

Deep Learning: The External Contextualization Engine Behind The Self-Driving Car

I’ve Got This Down to a Data Science

How Many Crowdsourced Experts Can Compute on the Head of a Problem?

Internet of Things and the Principles of Personal Data Exploitation

Inflecting and Genuflecting Toward Yet Another Analytic Industry Turning Point

The Swarming Nano-Agents of Algorithmic Cognition

Cognitive Computing and the Emerging Ecosystem of Algorithmic Savants

Fluid Is as Fluid Does: Automating the Machine-Learning Pipeline

Stuff You May or May Not Do With Whatever Data You May or May Not Possess

From REST to Restless: The Probabilistic Fabric of Cognitive Integration

The Sisyphean Challenge of Content Curation in a Big Data Universe

Top Trends to Watch in Cognitive Analytics in 2016

Deploying Analytic Microservices In The Internet Of Things