FarmBot is an opensource and scalable automated precision farming machine and software package designed from the ground up with today’s technologies. The world’s population is growing and is projected to surpass 9 billion inhabitants by 2050. As a result farms must increase production by about 60 percent to meet demand which is stunning since many believe we have reached the limits of traditional farming.
In comparison to desktop digital 3D printers and CNC machines FarmBot extends the idea of X, Y, and Z directions and applies it to plows, seed injectors, water and sensors in order to accurately and efficiently grow plants and soil. I think that I would like to try this out in my own backyard.
Continue reading “FarmBot: Opensource precision farming”
Actionable Intelligence: A Guide to Delivering Business Results with Big Data Fast! falls into the must read category for leaders of any organization. Actionable Intelligence is in the Lean model well beyond the vanity metrics that so many leaders have embraced. Lessons on implementing a secure framework comes from lessons including Estee Lauder, Procter & Gamble, Lifetime Brands and the CIA. Yes the CIA.
Reading this book I have found tested lessons by Keith B. Carter regarding the lack of Actionable Intelligence in many organizations. The start always seems to be the lack of organized data and determining which is the most pressing to actually use in order to be successful in a fast changing world.
Maybe his most powerful work revolves around how executives at any company (or university) even question the value of actionable intelligence regardless of the tools already in place. Too many silo examples reinventing the wheel while overlooking the need to understand their own data reporting methods.
Sustaining delivery of actionable intelligence by the evolution from Dashboards to Cockpits. IMHO to many university leaders are just beginning to understand the Dashboard and their tools miss the Cockpit opportunities.
Business lessons alone describe how to mine actionable intelligence prove the validity of this book. Lessons from Estee Lauder include how the company was able to leverage secure data reporting in order to adjust following the powerful Japanese earthquake and tsunami that triggered the Fukushima Daiichi nuclear disaster. And in some ways Carter points to a crisis in order for executives to embrace actionable intelligence:
People do not trust data, they trust other people and their opinion of the data. So when the data owners, the people who input the data and/or use it, raise their hands and say, “This data is good; I trust it,” that will make it more likely for other people in the organization to believe it. It also means that it’s clear. It’s not just that they trust it from the point that 1 + 1 = 2. It is also clear how the data has to be used, and the definition of the data is clear.
Carter helps breakdown the old data principle “People don’t trust data – they trust other people.” Its true. Estee Lauder’s use of actionable intelligence is such that every organization should be striving towards in order to stay competitive.
Every company and school needs to add Need, Speed, and Greed: How the New Rules of Innovation Can Transform Businesses, Propel Nations to Greatness, and Tame the World’s Most Wicked Problems to their mandatory reading list.
Vajay Vaitheeswaran really understands the need for innovation, change and embracing new ideas in order for America to survive and thrive into the future.
This is especially true for those in aging markets like the auto industry and higher education.
Need, Speed, and Greed is divided into three sections: Why Innovation Matters, Where Innovation is Going, and How to win in the Age of Disruptive Innovation.
This is cover-to-cover reading for everyone. I really looked deeper at the closing chapter Can Dinosaurs Dance. While applied to the American auto industry, think about the strides made by Elon Musk and Google, the application of dramatic change fits quite nicely into many universities around the country.
Continue reading “Latest read: Need, Speed, and Greed: How the New Rules of Innovation Can Transform Businesses, Propel Nations to Greatness, and Tame the World’s Most Wicked Problems”
Just started reading Need, Speed, and Greed: How the New Rules of Innovation Can Transform Businesses, Propel Nations to Greatness, and Tame the World’s Most Wicked Problems.
Must say its another refreshing look at how we must innovate in today’s global world. Written by Vajay Vaitheeswaran of The Economist, it is providing so far excellent lessons for any company, non-profit, innovation center or educational organization.
Addressing global health and education is just the beginning. Need, Speed, and Greed is laying out how companies must adjust (via lessons from IBM, Google and P&G) or watch the world run you over and out of business.
The one thing Need, Speed, and Greed is making very clear: we are now able to collaborate in a global view with advanced technologies and new open business thinking to solve complex problems around the globe.
This is shaping up to be the kind of book every school kid in America should be reading.
While focused on the task of generating data for astrophysics Reliability Assurance of Big Data in the Cloud is a worthy read when focused around designing cloud service contacts.
The work of authors Yang, Li and Yuan surround capturing big data reliability, and measuring disk storage solutions including from noted cloud vendors.
Their work at Centre for Astrophysics and Supercomputing at Swinburne University of Technology focused on reducing cloud-based storage cost and energy consumption methods.
They also share the impact of multiple replication-based data storage approaches based upon Proactive Replica Checking for Reliability (PRCR). That was very interesting in their research data gathering.
I found Reliability Assurance of Big Data in the Cloud also supports moving data into the cloud across advanced research networks including Internet2.
Processing raw data inside the data center impacts network models (based upon available bandwidth) in their work. Their research gathers and stores 8 minute segments of telescope data that generates 236GB of raw data. By no means in the petabyte stage (yet) but it still sets a solid understanding of contractual demands on big data cloud storage.
My interest peaked around impacts developing knowledgeable contracts for cloud services. Their background regarding data gathering and processing should influence procurement contract language. This is even more applicable when applied to petabyte data sets and the SLAs regarding data reliability requirements. Never leave money on the table when scaling to the petabyte range. Must read for purchasing agents and corporate (and university) CPSMs.