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foodbot

April 2, 2019

Video: Amazon CTO Werner Vogels Visits Singapore to Talk AI With Inventors of the Rotimatic

Back when I worked at Gigaom, every year we’d invite Amazon CTO Werner Vogels on stage at our big cloud computing conference and interview him about the future of the Internet and distributed computing.

Nowadays Vogels is conducting his own interviews, heading out to far-flung locales to talk to innovators about how they are using cloud computing and AI to build products and change the world in ways both big and small.

It’s all for his new Amazon web show titled Now Go Build with Werner Vogels, and for his most recent interview, the cloud computing pioneer went to Singapore to talk to the inventors of the Rotimatic about why they built machine learning into a home food robot.

The video is a fun watch as Vogels visits with the wife and husband team of Pranoti Nagarkar and Rishi Israni in the middle of a bustling Singapore restaurant and later heads into the kitchen to try his hand at making his own rotis.

The conversation high point for me was hearing Nagarkar and Israni talk about why they decided to power what was, at first, a fairly simple automated roti maker with machine learning.

“I remember there is one particular phase where we tried to make it an embedded system where you have a fixed program that could run it and it could find out the right proportion of flour and water,” said Nagarkar, who came up for the idea of the Rotimatic after getting tired of making roti every day by hand.

“That wasn’t enough,” she said. ” You had to build machine learning in because every time you make a dough ball you learn something more about it and you use it for the next dough ball. It just kept making the machine better and better.”

Israni agreed and said they also realized machine learning would be necessary to ensure high performance of the robot over its lifetime.

“We see machine learning mostly in computer systems where things aren’t moving much” said Israni.  “Here with life, there is degradation in all the tolerances and all the parts, so the performance of parts keep shifting over time.

Eventually, the conversation turned towards the challenges of today’s food system.

“I’ve realized a few big problems with our world,” said Israni. “Seventy percent of illnesses are lifestyle disease-related, and they are primarily related to the type of food you consume.”

The other big problem is food waste. “One-third of world’s food is wasted,” said Israni.

Israni sees these two challenges are intertwined. “On one hand, you have people who are unhealthy who are maybe eating a little more than they need and the other you have people who are dying because of lack of food. We find that these two problems are prime problems to be solved by the kitchen of the future.”

How does a more technology forward kitchen helping solve these challenges? According to Israni, through shared data and more connected appliances.

“This is an information data problem,” he said. “We already know how to fix the knowledge gaps, but we can also execution gaps by building machines that are fully connected and exchange information with one another to delivery a cooking experience.”

Vogels agreed.

We also need “to see all of these devices as a platform and not only as a single function device,” said Vogels. “Software eats the world.”

“But you can’t eat software,” replied Israni with a smile.

You can watch the full video below:

Now Go Build with Werner Vogels – S1E2 Singapore | Amazon Web Services

June 28, 2017

Watch Sally The Robot Make My Salad

Yesterday at the FOODIT event in Mountain View, I had salad for lunch.

Why I am telling you this? Because unlike any salad I’ve had before, this one was custom built for me by a robot named Sally.

We’ve written about Sally before at the Spoon, but this is the first time I got to taste a Sally-crafted salad.  On hand to give me a tour and tell us about Sally was Chowbotics CEO Deepak Sekar.

You can watch the video of Sally making a salad above, but here are a few takeaways from my conversation with Sekar and Chef Kelly Olazar:

  • Sally allows the user to choose “chef salad” mixes or build their own using the twenty types of ingredients.  Users can also use an app to do greater customization of the salad.
  • The list price on a Sally is $30 thousand, but the company does offer discounts
  • Sally herself weighs in at 400 pounds
  • The product is targeted towards office cafeterias, universities and restaurants
  • Sally can make about 40-50 salads before she has to be refilled. Yesterday at the FOODIT event, they had to once and served 90 salads. Chef Kelly Olazar told me people were coming back for second salads later in the day (cheapsters).

Overall, I like the salad and was impressed with how quick Sally worked. While the robot’s price seems high, I figured that if could replace a worker and generate $500-$1000 a day in a busy cafeteria, the product makes sense financially in a high-volume food service location.

June 23, 2017

Behind The Bot: Meet Sure, A Chatbot That Recommends Instagram Food Hotspots

While some people get downright grumpy when it comes to seeing food pics posted in their Facebook and Instagram feeds, I’m one of those that actually enjoys them. In fact, when I see someone showing off a tasty platter from a local restaurant on Instagram, I’ll often make a mental note to check that place out if it’s in my town or somewhere I plan on visiting soon.

If you use Instagram food posts as a restaurant discovery tool like me, I have good news: there’s now a bot that looks for Instagram hotspots and surfaces them in the form of restaurant recommendations. The chatbot is called Sure, and it’s a Facebook Messenger chatbot that curates the most Instagrammed food and drink spots in your neighborhood.

I interviewed the Juraj Pal, the CEO of Sure, to hear about how the idea for the bot came together.

Where did you get the idea for your bot?

Our motivation was simple. We weren’t satisfied with the existing restaurant discovery and travel apps and we quickly started believing that we can build a much better product for the next generation, already spending more time in messaging apps.

Having grown up with internet, we have soon learnt that virtually anything was accessible on our fingertips. It opened up a whole world of opportunities for us. But at the same, it made us feel overwhelmed with choices and options.

At first we actually started with a spreadsheet full of restaurants, cafes and bars that we curated ourselves. And to validate the idea, we launched a simple SMS bot where users would text our number and we would reply manually to each message, recommending a spot from our spreadsheet.

By tying visual social content to specific food locations, are you tapping into how you think this is how Millennials and others choose food?

We knew that others tried to solve this problem and the space is crowded with big players like Yelp or Foursquare. But we truly believe that for the new generation, they just don’t get it.

We quickly learned that millennials trust their friends and influencers more than reviews from strangers on Yelp. Rather than providing endless results like Google, we turned to Instagram as our primary source of all recommendations.

Why did you choose to use Facebook Messenger vs other platforms?

Other than having 1.2B monthly active users, Facebook Messenger is inherently social which makes it easy for people to share with their friends.

The social aspect has however been important also from another angle. When it comes to choosing a place to eat out, majority of the people ask their friends or influencers who they can relate to. By being on a platform where our users naturally chat with their friends, chatbot has the potential to blur the lines between tech algorithms and word of mouth recommendations.

What is unique about developing for a chatbot vs. other AI platforms?

We’ve seen different roles evolve as we were building the chatbot. We for example spend much more time on copywriting and building the bot’s persona and empathy than designing flows.

Building chatbots also costs less and happens much faster. And this in turn allows us to ship our product faster and iterate based on feedback we get. And what I love the most about this experimentation is that we’re focused on value delivery, rather than building potentially useless product features.

Why a food-focused bot?

We decided to start by answering the ‘Where shall we eat?’ question once and for all. Food is a highly personal choice that represents who we are and ties us with a community. Also, in the digitalised world we live in today, eating out is one of the few experiences that we cannot replicate online.

And since people are used to asking their friends for food recommendations on Messenger, we though we could be that concierge friend for everything when you’re out an about.

What have you learned since people have started using your bot?

A lot! There are literally 1000 ways how a person can ask for a restaurant recommendation and trying to support that with natural language processing is hard. Based on this we decided to switch to more pre-defined text and using more GUI elements.

Also, people love to test the boundaries of a bot and eventually they want to break it. Hence it’s equally important to educate our users how to talk to a bot, as it is building a responsive bot.

Finally, the speed in which we were able to capture learnings and improve the experience based on real usage was incredible. As opposed to cross-platform app development, we can instantly ship updates to all of our users without any disturbance.

Tell us a little about yourself – is this your first bot? 

I’ve founded and sold a startup in the food tech space in the past but this is my first chatbot.

What do you have in store for Sure?

After we launched on Product Hunt and expanded Sure to 22 cities around the world 2 months ago, we joined the Just Eat food tech accelerator in London.

We’re currently working on bringing the Sure experience into group chats and making it even more contextual as we grow to become the ultimate concierge for everything when you’re out and about – from choosing a restaurant to ordering an Uber to get home from a bar.

Tell us about your recently launched Sure extension for Messenger

We know that the way we discover restaurants is often by asking one of our friends. But many times, choosing a place to go with your friends can turn into a frustrating argument. This was the main motivation for launching our latest feature, the Messenger Chat Extension. This allows all our user to take the Sure bot with them to any group chat on Messenger and instantly share our recommendations with their friends. With this, we’re hoping to put an end to the “Where should we eat?” ordeal.

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