Now Is The Time For You To Know The Truth About AIoT
So far we’ve had smart devices and smart software(AI), but now is the time to bind them together to unlock their potential
1989 marked a year when “The World Wide Web” was launched. Then, a huge number of machines were connected.
When GPS became viable between 1994 to 2000 the creation of unfathomable data happened along with the connectivity of network devices. An era when the term “Internet of Things” was first coined by Kevin Ashton, co-founder of Auto-ID Centre at MIT.
What strikes your mind when you think of the term IoT?
Perhaps a bunch of devices understanding each other via connectivity. Today, IoT allows us to connect independent devices, exchange data and allows us to even interact with each other. Now you can imagine the kind of data that these devices collect — this is where the envisioning of artificial intelligence comes into the picture.
The Internet of Things (IoT) has been around for quite some time. And Artificial Intelligence (AI) has seen more than its share of iterations as well. But the combination of the two? That’s something that’s just starting to garner its share of the spotlight. It actually involves the embedding of AI technology into IoT components.
You might have heard this term — AI. Here’s a brief introduction
In general, AI is a HW/SW system intended to replicate the way our intelligence works — i.e. as opposed to be using hardwired, pre-programmed input/output logic, AI aims to be able to dynamically define its decision-making process based on the environment, task at hand, previous experience and desired outcomes. This usually involves having sensors, or some kind of input channels, being able to recognize patterns, being able to learn, assess improvements in the outputs, and adjust the behavior to optimize the process, maybe even have opinions and such. Quite often (not always) neural networks are used for AI, because they are particularly good in these aspects.
AI has various domains — you can choose any specific problem/domain you are curious about. In AI, Deep Learning has been the most useful, and proven to provide potential solutions to quite a lot of real world problems. If you are interested in learning more about core AI, here’s some resources that would help you go from Level 0 to having a significant importance in this field.
1)To get you started — 3Blue1Brown Artificial Intelligence Series:- https://www.youtube.com/results?search_query=3+blue+1+brown+artificial+intelligence
2)The most recommended AI course:- Andrew Ng’s Machine Learning Course
3)Once done with Andrew Ng’s course:- I would recommend you do challenges on Kaggle. They will help you build your understanding by solving these challenges and you can be noticed as you work your way up.
4)Time for you to up your game:- This is your first step at being a professional. How? By gaining deep techie knowledge and tools that are used by AI experts. Apply to this AI skilling + internship program and take your career to a new high:- http://iotiot.in/aiinternship/
Edge- or Cloud-Based AI
There’s a misconception that edge computing will replace the Cloud. On the contrary, it functions in conjunction with the Cloud.Big data will always be operated on the Cloud. However, instant data that is generated by the users and relates only to the users can be computed and operated on the edge.
But there are still times when AI is better off in the cloud. For example, when AI is used to interpret an MRI scan or analyze geospatial data collected by a drone over a farm, we can harness the full power of the cloud even if we have to wait a few minutes or a few hours for the decision.
Cloud-based AI, however, has its issues. For instance, when a sensor in a chemical plant predicts an imminent explosion, the plant needs to be shut down immediately. In these situations, AI must be located at the edge, where decisions can be made faster without relying on network connectivity and without moving massive amounts of data back and forth over a network.
Now is the time to bring AI+IoT together
So, far I discussed about AI and IoT as two different entities and we also saw a comparison on where cloud AI vs edge AI stands right now. You see, both have their advantages. But the thing I didn’t tell you about Cloud AI is- it requires to be constantly connected to the internet. Think of it like this:-
Consider, your AI model is your brain and your body as a beautiful combination of unique and complex sensors. Here, your model i.e, your brain- it’s stored in Cloud. Now when you want to use your AI model- do a certain complex task using this combination of sensors(your body), you NEED internet to use your brain. This is just not acceptable every single time.
So what do we do? I’ve got a solution to this! How about we BRING intelligence to the sensors or devices that we use? This is what Edge AI brings with it. It offers us our AI model- our brain, be embedded onto our sensors.
But wait, is this possible? Could this thing be true that I am telling you?
This has been absolutely possible. I know you might be thinking about Google, Microsoft, Nvidia, etc when I talk about such kind of AI. But, that isn’t entirely true. They’ve been huge players of Cloud AI and have been making a shift towards Edge AI as of now and I think it would take them time and resources AND for you to experience it you would need to empty your pockets quite a bit. Disappointing? Feel behind because of this?
Well, I think you don’t have to wait wait for some more time and turn your attention towards them if you want to experience this emerging and hot tech RIGHT NOW. There’s one player that ticks our expectations when we hear about the Edge AI, the cool things it can do and even the advantages it provides to startups and ultimately a larger population. The time for it is RIGHT NOW, and for YOU TO take a look at it.
I would like to introduce to you — Shunya
Ever since decades we’ve been using stuff that’s been Made in China and for our developers- S/W and H/W, they’ve not been able to get their hands onto this cutting edge tech that the West first get’s to work on. And to overcome this technological disability, I would like to talk about Shunya and I think so should you. That’s quite a bold statement I made but here are the reasons why Shunya would be your choice:-
- You want to do an AI task which will require you to write lines of code which depends on how complex task it is. Shunya has your back as you would just have to write VERY few lines of code or literally NO-CODE, and that’s it! You have a cool AI feature developed.
- Say you want to interface different sensors in a organization that deploys IoT. That’s pretty challenging and sometimes gets annoying- interfacing these different sensors together. BUT, with Shunya, it’s as simple and fun that you could interface over 200 sensors.
- Or say you want to develop an application using AI+IoT components, that’s some heavy stuff right there. Well, with Shunya you just have to use these built-in API’s that would power-up you application/product.
- And boy is it Made in India!
Shunya has been developed for H/W and S/W startups centered around AI, IoT and businesses that seek to employ similar tech in their organizations, to help them with Proof of Concept(POC)/ MVP development, prototyping for their products. I think Shunya serves these purposes very well because it understands that many of the Edge AI, IoT startups need this support due to the various obstacles they face in not only developing the core tech but the availability of the resources they need to pull this feat. Not only this, you get to know the brains behind Shunya and the community support it offers.
We seek for connections and amazing people who do amazing things that brings value to a lot of people. And here’s how you could be connected to them by simply clicking on the links below. Right now is the time to be a part of community that are the makers of Shunya and if you want to really succeed, you need to succeed together because, GREAT THINGS ARE DONE BY A BUNCH OF GREAT PEOPLE.
https://share.hsforms.com/1pxEQDdYzR6Wc4dkClmugZA48dwm
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