Tuesday, December 26, 2017

Kobielus thought leadership posts in 2017

CIO playbook for 2018: Leading analysts break down the trends

Wikibon’s 2018 Artificial Intelligence Chipset Predictions

Wikibon’s 2018 Artificial Intelligence Predictions

Generative AI: The new power tool for creative pros

Wikibon’s 2018 Data Predictions

Wikibon 2018 Community Predictions

AI development toolkits will shift toward solution orientation in 2018

Robot-driven programming is the leading edge of development’s new era

Wikibon’s 2018 Developer Tooling, Services, and Practices Predictions

Big Data: Main Developments in 2017 and Key Trends in 2018

Deeper deep learning shifts AI from sci-fi to software

Amazon sets the public cloud pace at AWS re:Invent 2017: a Wikibon deep dive

Wikibon Trip Report: At re:Invent 2017, AWS Sets the Pace in the Public Cloud

Clarifying Enterprise Deep Learning Development Priorities

Assessing Deep-Learning Development Frameworks

Bringing Model Training Fully into Machine Learning DevOps

Evaluating Serverless Frameworks for the True Private Cloud

Building Applications for Hybrid Clouds

Trip report: At Pentaho World 2017, Hitachi Vantara refocuses data portfolio on edge analytics

Even data scientists are facing AI takeover

As deep learning frameworks converge, automation possibilities unfold

The tension between data science professionalism and automation

Modern infrastructure management: accelerating productivity through machine learning

Bringing Analytics to the Edge: A Cube Discussion with Hitachi Vantara’s Chuck Yarbrough

Adopting Serverless Computing for Cloud-Native Applications

Using Functional Programming to Build Serverless Cloud Applications

Atlassian Delivers More Deeply Collaborative DevOps Portfolio

Webinar Preview: Top Trends for Moving Your Data to the Data Warehouse in the Cloud

Giving Machine Learning Freer Rein to Design Next-Generation Communications Protocols

Wikibon Weekly Research Meeting Notes: Serverless Computing

Defining an Architecture for Automating Data-Driven Business Processes

Deepening Data Capital Through Cloud-Based Machine Learning and Artificial Intelligence

Modern Infrastructure Management: Accelerating Productivity Through Machine Learning

Tuning Chatbots for Maximum Impact

Getting Started with Chatbot Development

Wrapping Our Primate Brains Around AI’s Next Grand Challenge

Putting “AI-First” Into Its Proper Context

Training Your AI With As Little Manually Labeled Data As Possible

How to prevent the hacked AI apocalypse

Maintaining the Business Logic That Drives Recommendation Engines

Data is eating the software that is eating the world

Developing the Business Logic That Drives Recommendation Engines

Digital twins will revolutionize the Internet of Things

Infor Launches AI-First Cloud ERP Strategy

Industry Initiatives Pushing AI-Infused Software to the Federated Edge
How to write event-driven IoT microservices that don’t break

AI-Infused Software Is Eating the IoT Edge

Pushing Storage to the Intelligent Edge—Recap of #ClearSkyEdge Crowdchat

Wrapping DevOps Around the Data Science Pipeline

Machine Learning Will Do Auto-Programming’s Heavy Lifting

Further Evidence of IBM’s Strategic Retrenchment in Enterprise Analytics

7 Ways to Get High-Quality Labeled Training Data at Low Cost

Automating Development and Optimization of Machine Learning Models

At Spark Summit, Databricks Pushes Apache Spark Where It Needs to Go

Automated Machine Learning Is the Key to AI Developer Productivity

Building AI Microservices for Cloud-Native Deployments

Agile Development in Team Data Science

Keeping cloud-native DevOps from spinning out of control

Istio: An Open Microservice Mesh for the Cloud-Native Era

Grasping How Graph Fits Microsoft’s Intelligent Edge Strategy

At Build, Microsoft delivers AI to mainstream software developers
The Container Ecosystem Accelerates Up Its Maturity Curve

Adding Data Science To Application Development

Self-programming machines will usher in the third age of computing

Get ready for application modernization, Docker style

Docker’s Application Services Ecosystem Is Still Underdeveloped

Looking Ahead to DockerCon17

Optimizing Your Application Architecture At The Federated Edge

Wikibon Angles April 6 2017:

Application Decay and the Burden of Data-Driven Algorithm Training

Putting Together A Full-Blooded AI Maturity Model

Scrutinizing the Inscrutability of Deep Learning

Homebrewed Deep Learning and Do-It-Yourself Robotics

Composing Deep-Learning Microservices for the Hybrid Internet of Things

Fundamentals for sure-fire cloud data warehouse optimization: An interview with James Kobielus

5 reasons to attend InterConnect 2017

Cooperative Trust Among Neural Networks Drives Deeper Learning

Don’t let Agile methods undermine data science

Will Data Scientists Automate Themselves Out of Jobs?

6 predictions for the future of deep learning

InterConnect will connect you with unstructured content governance

James Kobielus, IBM - IBM Machine Learning Launch - #IBMML - #theCUBE

Machine learning beyond data scientists: the self-serve model emerges | #IBMML

Machine learning enriches the private cloud

InterConnect will connect you with NoSQL Polyglot Persistence

InterConnect: Connecting you with collaborative data science, data engineering, and data app development

How Spark Illuminates Deep Learning

Machine learning in the evolution of data science

Machine learning in the private cloud

Going beyond collaboration to achieve data-driven success

Machine Learning and Statistical Algorithms: Training With Everything We’ve Got

Neuromorphic chipsets are shifting deep learning into overdrive

'Transfer learning' jump-starts new AI projects