These are the top 5 best Robots

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Buddy :
Ez Robot JD :
Romeo :
Personal Robot :

This video describes the reasons to become a software engineer!


A ride in a Waymo driverless car:

Full Self-Driving:

ITRI shows OLED Lighting, Chess playing robot “Turk”:

Artificial justice: would robots make good judges?:

This video is for non-commercial use.

Discussing Facebook shutting down an artificial intelligence bot and whether we should be concerned about the future of the technology with Martin Ford, “The Rise of the Robots” author, and RJ Assaly, Kensho Technologies product manager.
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Should We Fear A.I. Evolution? | CNBC

#Cybersecurity #Hacking #degree

What’s up #SecurityNinjas!

If you’re considering a degree in Cyber Security, please do the research on the program you’re considering.
Often times schools will advertise their awesome Cyber Security Major, and then it turns out to be a waste of time.

Links to well recognized Cyber programs:

Cyber Operations:

Cyber Defense – by state:

Music in this video:
Free Download / Stream:
Song —- Ark
Artist — Ship Wrek & Zookeepers

“AI isn’t magic, it’s just math under the covers.” We should all be responsible and ethical while using data and Jennifer Marsman gives some good reasons for that.

See Jennifer’s presentation from WROC# 2019:

( ** AI & Deep Learning with Tensorflow Training: ** )
This Edureka video on “Deep Learning Frameworks” ( provides you an insight into the top 8 Deep Learning frameworks you should consider learning

00:38 Chainer
01:40 CNTK
03:12 Caffe
04:46 MXNet
05:55 Deeplearning4j
07:42 Keras
09:21 PyTorch
10:45 TensorFlow
12:10 Conclusion

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#PyTorch #TensorFlow #DeepLearning #Python

Got a question on the topic?
Please share it in the comment section below and our experts will answer it for you.

About the Course
Edureka’s Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.

– – – – – – – – – – – – – –

Who should go for this course?

The following professionals can go for this course:

1. Developers aspiring to be a ‘Data Scientist’

2. Analytics Managers who are leading a team of analysts

3. Business Analysts who want to understand Deep Learning (ML) Techniques

4. Information Architects who want to gain expertise in Predictive Analytics

5. Professionals who want to captivate and analyze Big Data

6. Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.

– – – – – – – – – – – – – –

Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world.

How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

– – – – – – – – – – – – – –

Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.

For more information, please write back to us at or call us at IND: 9606058406 / US: 18338555775 (toll-free).

Check out 10 of the most awesome Artificial Intelligence (AI) startups in India
We focus on a diverse field of AI startups, including startups from Healthcare, Logistics, FinTech, among others
Any AI startup we missed? Let us know in the comments!

Write to us at:

Conversational AI Startups:
2. Avaamo

Healthcare Startups
1. Niramai
2. Doxper

Logistics Startups
1. LogiNext

Fintech Startups
1. Rubique
2. LendingKart

Other Awesome AI Startups
1. CropIn
Chatbots are ubiquitous these days. From businesses to the research lab, they have become an integral part of an organization’s strategy. Learning how to create a chatbot from scratch is a much-vaunted skill in data science.

Avaamo is another conversational startup that is currently serving six industries: Insurance, Financial Services, Healthcare, Telecommunications, Retail.

Founded in 2014, Avaamo has created a name for itself in around 40 countries now. Pretty impressive!

This AI startup will resonate with a lot of you. Healthcare is one domain where AI needs to make its mark. Progress has been slow due to various reasons but things have been looking promising in the last couple of years.

NIRAMAI stands for “Non-Invasive Risk Assessment with Machine Intelligence”. In Sanskrit, Niramai means being free from illness. It is a novel breast cancer screening solution

Doxper is another Indian AI startup working in the healthcare sector.

Have you ever seen hospital records? Keeping the records of patients is a hectic task – it is truly a formidable function. Doxper helps in simplifying the way healthcare data is recorded.

AI has left no stone untouched. It has found its niche in almost every sector, even the previously gigantic and manual logistics field. There are quite a few AI-powered logistics startups springing up and LogiNext is definitely among the leaders right now.
Another logistics startup in the list is Locus. Started back in 2015, the company provides facilities like route planning and optimizing, real-time fleet tracking, insights and analytics, and automated shipment sorting and rider allocation.

AI in finance just intuitively makes sense. Finance is all about number crunching (well, almost!) and machines are well equipped at this point to work with numbers. It is a perfect match. So it’s no surprise that the FinTech sector has seen a massive surge in AI applications.

LendingKart is another brilliant startup tackling the financial sector by providing loans to small businesses. Spread over 1300+ cities, LendingKart is on its way to becoming one of the leading FinTech companies in the world. Here’s their official statement:

The agriculture sector is synonymous with Indian values. It is an integral part of this country and what we are all about. So what can AI do to accelerate progress in this field? CropIn, a Bengaluru-based startup, provides a glimpse into the future of agriculture.
Imagine an AI helping you perform online transactions end-to-end. Sounds too futurustic to be true. But here’s the good news – it’s already here!


As an emergency doctor, I often find myself in the heartbreaking position of telling patients that they are much closer to death than they knew. Without that knowledge, and therefore without a plan for the kind of death they want, people often receive aggressive, uncomfortable medical care—even when they don’t want it. The ability to predict death is the stuff of myths and legends, but it’s much closer than we think: machine intelligence can provide precise predictions on a range of critical medical outcomes, and ease a great deal of suffering in the process. But do we really want those predictions? And what does better prediction with AI mean for the medical field? Ziad Obermeyer is an Assistant Professor at Harvard Medical School and a practicing emergency physician at the Brigham and Women’s Hospital, both in Boston.

His work uses machine learning to solve critical problems in clinical medicine. As patients get older and more complex, the volume of health data grows exponentially, and it becomes harder and harder for the human mind to keep up. Dr. Obermeyer’s work is focused on applying machine learning to find hidden signals in health data, and help doctors make better decisions and drive innovations in clinical research.

He is a recipient of an Early Independence Award from the NIH Common Fund, and a faculty affiliate at ideas42, Ariadne Labs, the Institute for Quantitative Social Science at Harvard University. He holds an A.B. (magna cum laude) from Harvard and an M.Phil. from Cambridge, and worked as a consultant at McKinsey & Co. in Geneva, New Jersey, and Tokyo, before returning to Harvard for his M.D (magna cum laude). This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at

The Church – His Body

Ginni Rometty, the Chief Executive Officer of IBM, sits down with Fareed Zakria to discuss artificial intelligence and what it means for the future of work. We should be clear about the purpose of these technologies, says Rometty, and they should be in the service of mankind. The conversation was originally published on January 18, 2017.

Please watch: “How Facebook targeted advertisements track you online, offline and where they sell your private data”

Elon Musk – “merge with machine”. Should we become cyborgs?

What do you think when one of the greatest entrepreneurs of all times, Elon Musk, says humans must merge with machines? Artificial intelligence, machine learning, and humans becoming cyborgs. This is no longer a science fiction. According to Elon Musk, humans must merge with machines or they face becoming irrelevant. The claim that people will eventually turn into cyborgs is no longer a crazy science fiction. But what happens when humans merge with machines? Artificial intelligence is making such an important progress now that humans will have to significantly change their ways of lives. Machine learning is process that we must take under control. One way to do is that we merge with robots It is possible that with the advancement of artificial general intelligence, the only plausible scenario for human race is to become cyborgs – merge with artificial intelligence and stay in control of it.

Elon Musk merge with machines

Otherwise, if we build AI separately, we would necessarily have to deal with what to do when robots become smarter than us by several orders of magnitude. This isn’t to suggest that robot would kill us like it’s most popular in movies. Even though Elon Musk said that artificial intelligence could wipe out humans. But the economic difficulties that come with any economic revolutions must be addressed properly. What do we do when autonomous machines take over most of our jobs? From self driving (or more precisely, autonomous) cars, through AI in medicine, design, and pretty much all low skilled jobs, we are going to face existential challenges as soon as next couple of years.

Of course it is possible that we wouldn’t build an AI but that’s not a benign scenario either. The only thing that would prevent from creating artificial intelligence is an event of a natural disaster, like climate change, or a major interstate war. But if we don’t boil ourselves to death or nuke our planet into oblivion, AI is a serious concern.

It’s certainly a great innovation that is capable of creating Star Trek abundance. But we need have to do this right. Musk proposed that we should unanimously ban use of AI for military purposes across the globe. But what if just one actor disagrees? Will everyone just trust each other? On the other hand, if we don’t prevent creation of another potential of destroying life on Earth, should even proceed?

These are some but not all of the questions that we need to have answered by the time we get to the age of robots smarter than humans.

What do you think? Should humans merge with machines? Would you want to become cyborg? Do you agree with Elon Musk on artificial intelligence? As Elon Musk says could artificial intelligence wipe out humanity? What do you expect from the age of artificial intelligence? Is Musk a cyborg? 🙂 I hope you like my thumbnail where I tried to turn Elon Musk into cyborg. The idea was to suggest that Elon Musk merges with robot. I used a picture of a Terminator and blended it together with Musk’s face. Now it’s Elon Musk Terminator 🙂

Humans must become cyborgs to survive says Musk

Elon Musk: Humans must merge with machines or become irrelevant in AI age

Artificial intelligence, human brain to merge in 2030s, says futurist Kurzweil

Merging humans with AI to create superior cyberbrains

Neural lace has been invented to organically connect your brain with a computer

Phantom, The Complex, Dark Times, Echoes of Times, by Kevin McLoed (
Dizzy Tracks by Chuki Beats

The footage and images featured in the video were for critical analysis, commentary and parody, which are protected under the Fair Use laws of the United States Copyright act of 1976.

Title: Strong AI: Why we should be concerned about something nobody knows how to build
Synopsis: At the moment, nobody fully knows how to create an intelligent system that rivals or exceed human capabilities (Strong AI). The impact and possible dangers of Strong AI appear to concern mostly those futurists that are not working in day-to-day AI research. This in turn gives rise to the idea that Strong AI is merely a myth, a sci fi trope and nothing that is ever going to be implemented. The current state of the art in AI is already sufficient to lead to irrevocable changes in labor markets, economy, warfare and governance. The need to deal with these near term changes does not absolve us from considering the implications of being no longer the most intelligent beings on this planet.
Despite the difficulties of developing Strong AI, there is no obvious reason why the principles embedded in biological brains should be outside of the range of what our engineering can achieve in the near future. While it is unlikely that current narrow AI systems will neatly scale towards general modeling and problem solving, many of the significant open questions in developing Strong AI appear to be known and solvable.

Talk held at ‘Artificial Intelligence / Human Possibilities’ event as adjunct to the AGI17 conference in Melbourne 2017.

Assessing emerging risks and opportunities in machine cognition

With AI Experts Ben Goertzel, Marcus Hutter, Peter Cheeseman and Joscha Bach.

Event Focus:
Given significant developments in Artificial Intelligence, it’s worth asking: What aspects of ideal AI have not been achieved yet?
There is good reason for the growing media storm around AI – many experts agree on the big picture that with the development of Superintelligent AI (including Artificial General Intelligence) humanity will face great challenges (some polls suggest that AGI is not far). Though in order to best manage both the opportunities and risks we need to achieve a clearer picture – this requires sensitivity to ambiguity, precision of expression and attention to theoretical detail in understanding the implications of AI, communicating/discussing AI, and ultimately engineering beneficial AI.

Meetup details:

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Kind regards,
Adam Ford
– Science, Technology & the Future

Searching a image when you know the name is possible.
But if you want to search for a name if you have only image or logo then what ?
Google has a feature called google goggle.
This feature helps you detect the name of the logo.
This software works on Artificial Intelligence.

Trainer: Navin Reddy

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Navin Reddy

Artificial Intelligence and Biotechnology are redefining what it means to be human, and succeed in life and work. Education curricula must be deeply redesigned for versatility and adaptability, implying all of the four dimensions of Knowledge, Skills, Character and Meta-Learning, and the interplay between them. Our future requires holistic humans who are like “Swiss Army knives”: multi-faceted capabilities in many domains, broadly and deeply, with the ability to continuously reflect and adapt by having “learned how to learn”. Charles Fadel is a global education thought leader and author, futurist and inventor; founder Center for Curriculum Redesign; visiting scholar Harvard GSE; chair education committee BIAC/OECD; co-author “Four-Dimensional Education” (now in 15 languages) and best-selling “21st Century Skills”; founder Fondation Helvetica Educatio. He was formerly: Global Education Lead at Cisco Systems, worked with education entities in thirty countries; visiting scholar at MIT; angel investor. Holder of BSEE, MBA, 7 patents. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at

Computers already play games such as Super Mario Bros or chess better then humans do. But can they understand emotions and interact with humans? Or even become smarter than the human race? In his insightful talk, 22 year-old Daniel Dippold shows how a computer plays Super Mario and discovers the rules all by itself. He explains that society has not clearly defined what AI is yet and appeals urgently to the viewers by suggesting an open and broader discussion on the philosophical and ethical aspects of AI.

Daniel is a motivated and easygoing young individual. He is president of The Kairos Society in Switzerland, entrepreneur of two companies which are in their seed stage, and a productivity, performance and fitness coach. He has worked in South Africa, Australia, Switzerland and Germany. He holds various Board Positions, such as Vice President at Toastmasters SG, Partner at YouKnow and Member of the Supervisory Board at Project, a 400 employee corporation. Prior to that, he has been part of organising the St. Gallen Symposium, a platform for intergenerational debate (, and START Summit, Europes biggest student-run entrepreneurship conference ( His grades at the university score in the highest percentile (99%). Though studying business, his areas of interest are the realms of AI, neurology and productive psychology (esp. habits).

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at

BCG Partner and Managing Director Philipp Gerbert presents on the benefits of AI to a group of senior leaders at MIT.

Welcome to the official YouTube channel for The Boston Consulting Group. Since 1963, BCG’s experts have been helping businesses, governments, and non-profit organizations build lasting advantage. As a leading management consulting firm, BCG empowers clients to make the changes needed to seize the competitive advantage and win. The independent spirit handed down from Bruce Henderson, BCG’s founder—always challenging the status quo—has given the firm the courage to look beyond the obvious in pursuit of lasting solutions for our clients.

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