Technology in Farming – Robots, Mixed Reality, Machine Learning

Is manual farming sustainable as the need for agricultural products grow in demand? Can technology help? How does it impact lives of farmers? Is it the right thing to do? Like any other applications of technology, there are more questions than answers. The following links are just a set of leading indicators of trends.

Agricultural vehicles known as “cucumber flyers” enable as many as 50 seasonal workers to harvest crops.
Experts from Fraunhofer IPK in Berlin, along with other German and Spanish researchers, are studying the potential for automating cucumber harvests in the scope of the EU project CATCH, which stands for “Cucumber Gathering – Green Field Experiments.” Project partners are the Leibniz Institute for Agricultural Engineering and Bioeconomy in Germany and the CSIC-UPM Centre for Automation and Robotics (CAR) in Spain.
During the Hands Free Hectare project, no human set foot on the field between planting and harvest—everything was done by robots. This includes:
  • Drilling channels in the dirt for barley seeds to be planted at specific depths and intervals with an autonomous tractor;
  • Spraying a series of fungicides, herbicides, and fertilizers when and where necessary;
  • Harvesting the barley with an autonomous combine.

How mixed reality and machine learning are driving innovation in farming

The Economist, in its Q2 Technology Quarterly issue, proclaims agriculture will soon need to become more manufacturing-like in order to feed the world’s growing population. Scientific American reports crops will soon need to become more drought resistant in order to effectively grow in uncertain climates. Farms, The New York Times writes, will soon need to learn how to harvest more with less water.

Some Ideas for a Newbie Tweeter

I am always urging people who would listen (and even people who would not ) to blog, tweet or learn Python. A friend of mine, who finally bought into my idea asked me “What should I tweet about”. I wrote a list. I thought it may be useful to others too. So I am sharing it here.
 
I assume that you know your target audience. When you start out, you may not know. Make your best-educated guess but confirm it as you tweet and get responses.
 
  1. Tweet about your professional self. Especially, lessons you learned that you think may be relevant to your audience. 
  2. Tweet about your profession. Talk about what aspects you enjoy most.
  3. Tweet about events. Not just that the event happened but what caused it, what you see as the effect of such events.
  4. Tweet about your learning (related to your profession). 
  5. Advice to my younger self is a nice format in which you can share your insights and wisdom about life. 
  6. Share little bits of knowledge. A one-pager or a paragraph of about a topic in your industry would be a great start.
  7. Share tweets you like. Please annotate it with your observations.
  8. Ask your audience a simple open question and start a conversation. Use a hashtag to watch these conversations. 
  9. Tweet about something worth reading, listening to or watching. Mention why you are recommending it.
  10. Tweet about ideas and trends in your industry and their potential impact. This can be another interesting conversation starter.
Please share your ideas on tweeting. If you write blog posts, please tweet them and use #tweetideas as a hashtag.

5 Reasons Why Should You Host An Hour of Code

I was talking to a group of faculty members at KCG Tech on why we should ask schools to host An Hour of Code.

The Hour of Code started as a one-hour introduction to computer science, designed to demystify “code”, to show that anybody can learn the basics, and to broaden participation in the field of computer science. It has since become a worldwide effort to celebrate computer science, starting with 1-hour coding activities but expanding to all sorts of community efforts.

Here are some reasons why you should be interested in hosting an hour of code or help schools to host it.
  1. This grassroots campaign is supported by over 400 partners and 200,000 educators worldwide.
  2. It is an international movement to get people interested in learning to code.
  3. The first step in teaching programming is to get the learner engaged. Next steps include creating curiosity and giving them a sense of wonder. Show them what they can do with the code in a few minutes.
  4.  Students will do something different and have a lot of fun while learning. In the past couple of instances where we conducted an hour of code, many 7th graders went beyond the hour, refusing to leave the computer lab.
  5. The program will be run mostly by student volunteers and techies. We are trying to get students involved in social causes. We believe the best form for students to learn, is by teaching.

What do Product Managers do?

The term “Product Management” evolved somewhat. For me, it was a confusing term. Product Managers (AKA PMs) did not fit into either development or marketing roles. I list three good articles that demystify Product Management.
  1. Evolution of the Product Manager
  2. The Product Manager Contribution
  3. How product managers are becoming mini CEOs

There are also two books I like.

Product Management Books - Inspired

 

My son suggested that I read Inspired.  A few days later, I forgot the title and was searching for books on Kindle, when I found 42 Rules.

product managment books - 42 rules

Reading them, I realized that:

Product managers play the role of glue between customers, products, marketing, sales and engineering.

List of 100 – A Great Tool for Thinking

There are several cool tools you can use for thinking.  Two of my favorite ones are Mindmaps and Lists.

List of 100 is a great way to really stretch your mind. Here is how you do it.  Take a problem or idea. Create a list of 100 things that come to your mind. In the case of a problem, it may be a hundred ways to solve it.  In the case of an idea it may be a list of hundred thoughts (typically questions related to – Why, What, Who, When, How, Where).

I first came across the List of 100 here. Since then, I have created lists of 100 individually and in groups. We had great fun doing it and learned a lot. List of 100 is both a thinking tool and a group collaboration tool. Give it a try.

7 Things I Learned from Listening to The Culture of Innovation Talk

I really enjoyed watching  “The Culture of Innovation” from MIT Technology Review.

The talk covers several interesting topics worth exploring.

  1. Permission less innovation and Innovation at the edges
  2. A culture of practice over theory
  3. The concept of Social Investing
  4. Connectivity in Communities
  5. Peripheral vision and Pattern Recognition and how they are the total opposite of focus and execution
  6. Attachment bias
  7. Cultures and sub-cultures

My favorite quote from the talk:

We so cherish focus, execution and they are the opposites of peripheral vision, pattern recognition
Peripheral vision and pattern recognition lead to discovering new ways of doing things.
Here is a link to the video interview with Joi Ito.

Thinking Through the Design of a Product is Fun

I was talking to a student. He is fascinated with a robot that cleans pipes. He had a prototype and won some awards. He wanted to discuss it.

We sat with him and brainstormed many ideas for the design at a very high level. I encouraged him to think about a different cleaner robot – one that cleans water tanks. Our discussion lasted half an hour and it was one of the most rewarding exercises I did today.

Thinking through the design of products is fun. When you do it as a small passionate group, it is even more fun. One of the reasons I hang out with a lot of engineering students.

Learning Without Learning

Most of my school and college life was spent in learning lots of facts. I also learned principles and concepts but not in any coherent manner. I was not sure why I was learning, what I was learning. Our teachers (if they knew), forgot to tell us the “Whys?”. Some of this learning was fun and enjoyable and reasonably effortless but some of it was not.
When I started working, I started learning by doing. This was way more fun since I had a context on why I had to learn certain things. I retained my knowledge better since Iusing it. When you learn by doing or learn so that you can use it, the style is very different. You learn on demand and if some of what you are learning does not make sense, you dig deeper and try to find out why something works the way it does. I will call this as exploratory learning and it certainly is a lot more effective.
I think people will learn better, if:
  1. They know why they are learning (learning by understanding the larger context)
  2. They are allowed to explore (learning by exploring and discovering)
  3. They are challenged by tasks that require learning (learning by doing)
  4. They have the freedom to learn in their own ways (Seven freedoms of Learning)
  5. We make learning as interesting as playing games
 If you are interested in this topic, please see How People Learn and Seven Freedoms of Learning.

Where is Machine Learning Being Applied?

When I give talks on Machine Learning, I often get these questions:

  • What is Machine Learning?
  • What are some Machine Learning Applications?
  • Is Machine Learning Mature?
  • Who is using Machine Learning?
  • How do we get started?

If you are using Google or Bing Search, if you get recommendations for books or other products from Amazon, if you are getting hints for the next word to type on a mobile keyboard, you are already using Machine Learning.

Here is a sample list of Machine Learning applications.

From  Apple’s Core ML Brings AI to the Masses:

  • Real Time Image Recognition
  • Sentiment Analysis
  • Search Ranking
  • Personalization
  • Speaker Identification
  • Text Prediction
  • Handwriting Recognition
  • Machine Translation
  • Face Detection
  • Music Tagging
  • Entity Recognition
  • Style Transfer
  • Image Captioning
  • Emotion Detection
  • Text Summarization

From Seven Machine Learning Applications at Google

  • Google Translate
  • Google Voice Search
  • Gmail Inbox Smart Reply
  • RankBrain
  • Google Photos
  • Google Cloud Vision API
  • DeepDream

Also, see – How Google is Remaking Itself as a “Machine Learning First” Company.

While Apple, Google, Facebook, Amazon, IBM, and Microsoft are the most visible companies in the AI space, take a look at business applications of Machine Learning.

What is Machine Learning?

What is Machine Learning? It is a common question that I get asked a lot. I wanted to find a simple, intuitive definition. After doing a few Google searches, I settled on this one from Arthur Samuel.

from Arthur Samuel (in 1959)

“[Machine Learning is the] field of study that gives computers the ability to learn without being explicitly programmed.”

It is a field of study. I like that.  I picked this after Googling and finding over 100 descriptions. Here is a shorter curated list of results from this Google Search.  From this list, you may find that Machine Learning is:

  • A technique
  • A field of study
  • An application
  • A Method
  • A type of AI
  • A sub-field of AI
  • A general term
  • A cure-all for all human problems (just kidding)
  • A data based application generator
  • A statistical method of learning from data
  • A mapping function of inputs to outputs

So, what do you think is Machine Learning?