The more we work in a focused way, the more connections we build between ideas, and the better we are at making progress. But making connections isn’t just a model of expertise. It’s a model for a life well-lived. The longer we live and work in one place and the more effort we put into our communities, the stronger and richer our connections to community become.
For many of us who’ve been at IBM a while, the culture goes deep. It’s a culture of intelligence, respect, professionalism, and inclusion. And as an outgrowth of those things, it’s also a culture of generosity and altruism. Srini Bhagavanhas spent over 20 years at IBM, absorbing that culture. I like to think it’s part of why he’s now pursuing a PhD in computer science and bioinformatics, with the deliberate aim of saving lives.
Most of us strive to be life-long learners, but what does that mean in practice? For some, it means going deeper and deeper into our chosen field, refining our expertise in chemistry, carpentry, or cognitive science. For others, it means always exploring in new directions.
One of the great pleasures of connecting with our team is hearing about the endeavors and ideas people explore when they’re not at work. With Peter Plachta, that was a special treat. Peter’s interests range across physics, rock climbing, behavioral psychology, and the leadership that makes teams successful — at IBM and elsewhere.
As life moves forward day by day, sometimes it’s easy to forget how far we’ve come — personally, professionally, or both. Consider Simao Liu who came from Beijing to San Francisco just seven years ago for a master’s program in computer science. In her second year, she joined IBM as a QA intern and has spent the last six years making remarkable progress through the organization.
I love my trips to IBM’s Krakow Lab. The city’s Old Town is alive with music pouring out of cathedrals, students strolling the Main Square in the evenings, and rowing teams slicing through the Wisla River at dawn — all watched over by a 14thc. castle on Wawell Hill.
There’s no one path to IBM, and no one path to becoming a designer. Whenever I travel to our labs and studios around the world, I meet employees who arrived at IBM from wildly unconventional backgrounds, using their unique pasts to inform the work they do every day. That’s been the case for Reena Ganga, a designer based out of SVL’s Design Studio, who spent the ten years before IBM working as a journalist and news anchor on Australian television. Over time, her impressive curiosity led her to the design field and a career at IBM.
A few months ago, I was talking with the CTO of a major bank about machine learning. At one point he shook his head ruefully and said, “Dinesh, it only took me 3 weeks to develop a model. It’s been 11 months, and we still haven’t deployed it.”
Db2 for z/OS is one the most business-critical products in the IBM portfolio and remains core to many transaction processing, advanced analytics, and machine learning initiatives.
Imagine being able to arrive at your destination as much as 200 times quicker or being able to complete your most important tasks as much as 200 times faster than normal. That would be pretty impressive. What if you could get answers to your analytics queries that many times faster and run your machine learning algorithms with maximum efficiencies on your data by simply plugging in a pre-configured and pre-optimized system to your infrastructure? That’s what the IBM Integrated Analytics Systems (IIAS) is designed to do.
I originally started the “You in the Private Cloud” series as a way to introduce our talented team to each other across our many geographies. I knew it was important for us to know each other as more than email addresses or voices during meetings.
But I didn’t realize at the time that it would become one of the favorite parts of my job. I truly love settling in for great conversations with the terrific people working on IBM Analytics offerings across the globe.
As much as I love meeting long-time IBMers and hearing their perspective on our evolution over the years, it’s a special pleasure to visit with our newer team members and to hear their visions for IBM’s future. You’ll remember my conversations with Martyna Kuhlmann, Ketki Purandare, and Phu Truong.
I have just finished presenting at the DataWorks Summit in San Jose. CA. where a partnership between IBM and HortonWorks was announced the aim of which is to help organizations further leverage their Hadoop infrastructures with advanced data science and machine learning capabilities.
All tech companies draw international talent, but arguably none more so than IBM. Our Analytics Development team alone has labs in Canada, Germany, India, Japan, China, and the US. It’s fascinating for me to hear first-hand the different paths you took to IBM; we are richer for your talent and for the different ways of thinking and for being you and what bring to the team. From Martyna, I learned what it’s like to live in a tiny village in Poland, steeped in the intimacy of village life and in Poland’s tradition of excellence in mathematics.
What a pleasure it was to meet Sebastian! He was recommended to me as a technical whiz with Python™ skills par excellence, but he impressed me just as much with his infectious, happy energy, his thinking on the advancement of society and technology, and how he chooses to spend his time sharing his passion for electronics and software with children and adults at his local community center.
My most recent in-flight reading was Thank You for Being Late. In it, Thomas Friedman says risk of AI isn’t that it’s going to take over humanity, HAL-like, but that we as humans could become so entranced by technology that we’ll neglect to teach it human values. It’s not machines v. humans or technology v. creativity. The more technology develops, the greater the opportunity to add to it our kindness, our fairness, and our creativity.
With many of the top banks, retailers, and insurance organizations using IBM® z Systems® , combined with tried and tested virtualization capabilities, EAL5+ security rating and the ability to handle billions of transactions a day, the platform becomes attractive as a private cloud for running advanced analytics as well as cloud managed services.
Readers of this blog know that I like to imagine the world through the eyes of my young son. His effort to find the right balance of exploration and safety resonates with what we mean by “private cloud” and preparing clients for a hybrid cloud environment: private plus public.
Our Chief Designer, David Townsend, takes new designers aside when they join our team and tells them, “This is the most complicated thing you’ll ever design. Don’t be afraid to ask dumb questions. And know that everything else in your career you design after this will be easy compared to what you’re about to do.”
If you’ve seen the movie “Hidden Figures” — and if you haven’t I highly recommend you do, and not just because IBM is a central character — you’ve seen how the race to get a man into space was profoundly affected at the 11th hour by one courageous woman, and the help her boss, her friends, her teachers, and her family gave her to get to that one minute in time when she made a difference.
My founding principle for our organization is, “people first.” I believe that to build great products, you start with talented people and invest in their work and their individual well-being. The great products they make will in turn bring customers.
It seems to me that more and more companies are adding Apache Hadoop to their mix of technologies in attempts to spend less time in the creation of an Hadoop infrastructure and focus more on gaining the benefits. IBM BigInsights (our implementation of Hadoop) is ready to take on that challenge. It provides a complete solution that is not only open and combines Hadoop and Spark, but also provides the right tools to help make Big Data easier and more scalable, while integrating it seamlessly with SQL, noSQL and other data types.
Apache Spark™ puts both deep and broad advanced analytics capabilities in the hands of the masses. Whether a data scientist, data engineer, analytics app developer or citizen analyst – Spark delivers sophisticated analytics simpler, faster and more efficiently than ever before.
In my last blog “Business differentiation through Machine Learning” I introduced and described the concepts of machine learning. We traced its origins from a computer science project to Watson showcasing and winning on the Jeopardy TV quiz show and its real world use across numerous industries including health care.
I look at my child and marvel as he embraces the ever fast moving world around him, adapting to new experiences, grasping technology, absorbing a bombardment of information from so many sources. It’s staggering to watch their progress from basic learning of just accepting facts they are taught, to augmenting those facts with their own knowledge, to asking questions, using their knowledge to express their opinions and values to others, then challenging facts and hypotheses that they once accepted to adapting their knowledge, understanding, decisions and value systems.
The origins of Apache™Hadoop® go as far back as 2003 in reference to the emergence of a new file system, followed by the introduction of MapReduce and the birth of Hadoop in 2006. It achieved notoriety and fame as the fastest system to sort a terabyte of data and when it became an Apache open source project (Apache Hadoop) it sent a signal that it was ready for prime time. The world never looked back.