I used to think ML would be daunting and boring. Instead, Dale’s enthusiasm and daily life applications of ML really illustrate that this can be fun and approachable. 😲
One of the most beautiful advertisement I saw today. Thought it was about ML and not about selling Google products (and giving him the few spare things don't have yet)
Really amazed by Google Machine learning tools and your presentation skills👏👏. I'm looking forward to learn Google ML tools. Edit: That Hindi translation was too short to be judged for its accuracy, but the idea and the translated voice was quite impressive though. Google translated English text is not always that accurate. It has improved a lot though .
Wow.. the first use case 'make multimedia searchable', I have discussed it with colleagues many times. I just didn't know that the solution is already almost there.
This is so cool - it really illustrates a lot of key topics in ways that are useful and relatable. Thanks for sharing! You've also come along way from those first steps! ;)
What is "cool"? That software can detect bicycle in video and mark that second minute contains it? Or possible to find voice "hi dady"? Oh my, people who u are to be fascinated by such things... What's really shocking is that u believe this is "artificial intelligence"...
Pulling us with the cute baby videos and then amazing us with futuristic tools that make AI accessible... it was a good plan, and it worked on me! Interesting variety of tools here, but the video managed to flow smoothly from one to the other and give a taste for what's available in the API. 👍
Great video and nice hindi translation. What kind of mic you are using your voice is fantastic and very clear. These are great example for ML. Thanks for the video.
Is all this stuff available for the public or do you have to be a google developer, to have access. I wonder if you would do a walkthough of one of your demos, showing exactly how it's put together.
2:30 Sparkly biiiiike! :-) I agree that finding such moments is an excellent use case. My barrier right now is the cost of encoding & cloud storage, but I look forward to searching through old home videos (and film) someday.
Wow, amazing video, very inspiring! I liked how you explained how to use Machine Learning to solve real world problems 🤩I like the approach you did and the projects using Google Cloud Tools, everything amazing! PD: It's so nice you have a lot of recordings of your childhood and now you cand find them easily 😁
I have ZERO knowledge of ML and AI but found this video interesting. It may sound like a dumb question but what if videos don't have external tags, transcripts, and descriptions with them. How would you make sense of them using ML & AI tools? Thank you
The example in the video used a ML model from google. So it's basically just loading in the video, let the model do it's calculations and take the output. What the model does under the hood is very comlicated math - and also a lot nobody actually knows. In this example, it used some voice recognition to transcribe speech, propably image-recognition to identify certain objects and areas and then the word embedding to feed the search-engine. The word embedding is seperate because the words you write into the search are send through the same embedding algorithm - but obviously you wouldn't send those words through the image-recognition. Image recognition might be done on every image or once per second or maybe it identified a scale of "change" so that if the camera was filming the same spot for a minute, the model does only go over it once instead of 60 or so times. The reason this works is because Google used billions of images which were already tagged, have ML and AI scientists create a theoretical construct that should be able to learn identifying those -> and then have that construct do a massive ton of calculations and self-adjustments (the actual learning process) until it found the same tags in the images as provided. This training process might easily have taken days or even weeks. At the end, the model has "learned" to identify these things and can be used on data it has never seen before and hopefully find fitting tags as well. Just to reiterate, nobody knows what calculations the model is actually doing or why they work. Because during training it has finetuned millions, if not billions of parameters for calculations.
Awsome, I can now finally understand my boss's unorganized stock system that he used up to 10 different descriptions for the same item!! RUclips algorithm is doing a fantastic job this time.
Nice video which deserves a like....but Dale you have one privilege which I - as a common man - don’t have..which is ..you don’t have to pay for GCP services coz you work there 😊 …even the free tier does not help much-tell your bosses to make it affordable …
All that can be done locally, but she's advocating the benefits of using cloud and google ML APIs in particular. I personally love to apply ML to my daily life tasks to make it better and easier. For example the file searching example, I've made that so that it would scan the locally stored files, since that would be faster and given the bad rep that Google has regarding user privacy, I can't chance uploading my personal files and media to google drive, also it'd be a time and space consuming task.
I used to think ML would be daunting and boring. Instead, Dale’s enthusiasm and daily life applications of ML really illustrate that this can be fun and approachable. 😲
2:30 - finding specific memories in videos
6:19 - semantic reactor - google sheets
7:31 - Universal sentence encoder
The information density of this video is excellent! Really liked how you squeezed in so much into a relatively short video.
step one: share your entire life with google
step two: do stuff
Very inspiring Dale! Thank you so much. I'm new in this ML world and it makes me wants to do more with it
Google: who has their family videos since they were born?
Dale: me me me !!
google: ok you're doing our next TensorFlow video.
Ok Google. 😆
hahahha funny
Well, yah. Big yah.
What a great exposure to understanding how to start using and thinking about problems with machine learning. Definitely going to check it out!
The elbow pose over time in the video is pretty cool.
Use cases are of course great but I love this person the most
😍
Totaly agree! Great communication skills.
One of the most beautiful advertisement I saw today.
Thought it was about ML and not about selling Google products (and giving him the few spare things don't have yet)
Wow!
I don't know much about ML, and this is really inspired me to know more about AI and ML.
Thanks ❤️
It's a deadly road be tough😂 n don't give up
exactly! same for me
AI newbie here. Wow. Just wow! You had me since the AI read the icing on the cake.
Hindi version sounded pretty good to me. All the examples are pretty amazing
Very useful content fluently presented in a clear and personable style. (I'll be trying the video translation.)
Really amazed by Google Machine learning tools and your presentation skills👏👏. I'm looking forward to learn Google ML tools.
Edit: That Hindi translation was too short to be judged for its accuracy, but the idea and the translated voice was quite impressive though. Google translated English text is not always that accurate. It has improved a lot though .
Wow.. the first use case 'make multimedia searchable', I have discussed it with colleagues many times. I just didn't know that the solution is already almost there.
Eye opener introduction to TF application.
Amazing, inspiring and totally relatable examples....
This is so cool - it really illustrates a lot of key topics in ways that are useful and relatable. Thanks for sharing! You've also come along way from those first steps! ;)
What is "cool"? That software can detect bicycle in video and mark that second minute contains it? Or possible to find voice "hi dady"? Oh my, people who u are to be fascinated by such things...
What's really shocking is that u believe this is "artificial intelligence"...
Purely inspiring! Dale Markowitz you should start your own RUclips channel!
Watching your tennis serve example was really helpful. This could be also applied to other sports too...like say shooting a basketball?
Pulling us with the cute baby videos and then amazing us with futuristic tools that make AI accessible... it was a good plan, and it worked on me! Interesting variety of tools here, but the video managed to flow smoothly from one to the other and give a taste for what's available in the API. 👍
I just loved every bit of this video.
Great video and nice hindi translation. What kind of mic you are using your voice is fantastic and very clear. These are great example for ML. Thanks for the video.
You actually solved a serious problem. Thank you so much!
I liked this video by Dale. the presentation is simple and excellent. I feel it engaging and immersive. though I m non tech background.
Well I think this is best video so far I saw on why so much fuzz out there about ML.
Is all this stuff available for the public or do you have to be a google developer, to have access. I wonder if you would do a walkthough of one of your demos, showing exactly how it's put together.
What a great presentation! This is blowing my mind. I feel like a kid at a candy store. So many possibilities! Thanks!
Great preso.Would be greater if you could give some idea around cost for the stuffs built
How much was approximate cost according to you?
I don't know the initial speech but the Hindi translation was not *that* bad! Did the job pretty well
PHEW
This is a great talk and a great speaker!
I used python to convert text into speech ..once in a tiny project ..and it worked well .. that was easy too !!
Amazing! Thank you Dale!
How are you tracking position of your skeleton, you wrist, elbows, shoulder etc. in a video?
2:30 Sparkly biiiiike! :-) I agree that finding such moments is an excellent use case. My barrier right now is the cost of encoding & cloud storage, but I look forward to searching through old home videos (and film) someday.
Good Stuff!! The Hindi part was also very convincing.
Really interesting video Dale. fun to see what options google and Tensor has.
Wow, amazing video, very inspiring! I liked how you explained how to use Machine Learning to solve real world problems 🤩I like the approach you did and the projects using Google Cloud Tools, everything amazing!
PD: It's so nice you have a lot of recordings of your childhood and now you cand find them easily 😁
As always, a great and inspiring video! Thanks a lot
I have ZERO knowledge of ML and AI but found this video interesting. It may sound like a dumb question but what if videos don't have external tags, transcripts, and descriptions with them. How would you make sense of them using ML & AI tools? Thank you
The example in the video used a ML model from google. So it's basically just loading in the video, let the model do it's calculations and take the output. What the model does under the hood is very comlicated math - and also a lot nobody actually knows.
In this example, it used some voice recognition to transcribe speech, propably image-recognition to identify certain objects and areas and then the word embedding to feed the search-engine. The word embedding is seperate because the words you write into the search are send through the same embedding algorithm - but obviously you wouldn't send those words through the image-recognition.
Image recognition might be done on every image or once per second or maybe it identified a scale of "change" so that if the camera was filming the same spot for a minute, the model does only go over it once instead of 60 or so times.
The reason this works is because Google used billions of images which were already tagged, have ML and AI scientists create a theoretical construct that should be able to learn identifying those -> and then have that construct do a massive ton of calculations and self-adjustments (the actual learning process) until it found the same tags in the images as provided. This training process might easily have taken days or even weeks. At the end, the model has "learned" to identify these things and can be used on data it has never seen before and hopefully find fitting tags as well.
Just to reiterate, nobody knows what calculations the model is actually doing or why they work. Because during training it has finetuned millions, if not billions of parameters for calculations.
Great demo!! Thanks for sharing
Awsome, I can now finally understand my boss's unorganized stock system that he used up to 10 different descriptions for the same item!! RUclips algorithm is doing a fantastic job this time.
That hindi language generated video was really amazing 👍🏼. I think that was even better then what we speak here 😂
But the meaning was lost in translation.
Wow... this is one of those ideas that I actually want to use
Great video on machine learning application and very relatable
The Hindi part made me hit the Like Button 😊
She explaining everything so cool 🔥Dale Markowitz 💚
8,000
Very cool. Great idea about the applications of ML.
Really helpful..Thanks!
I loved loved loved this video!
good to see 'apple' and 'garbage can' is so close in embedding space chart
Nobody:
Google: Now I can relive those moments too
Wow, fantastic, thank you!
💥
Very nice video.Thank you!
Better use isolated virtual environment when testing the A.I solutions.
Very awesome video !!
Great talk Dale.
Loved it!!
This was awesome! Thanks
wow! great session. thankyou
amazing video
Just wanted to know which technique she might have used to convert text to vector..? Is it word 2 vec?
Probably. That is usually a best use case
We all have a excerpt from our life to associate with why we started using ML.
This is great, I love your videos, could you also include info around what the costs would be?
Superb video! Makes you yearn to learn more and more. ❤️
Such nice explanation in such easy language !!
Where is all the repository stored, it’s it in key value format ?
Great Work.. I've left earth..thanks for the cute family videos..
How can I learn algorithms to do myself? I don't want to use ready-made service, Instead, I want to learn to develop on my own.
This is such a good video!
Can we use this as projects Of Machine learning
How long did this app take & how many people worked on it?
I only know the Forrest tree diagrams.
Nice video which deserves a like....but Dale you have one privilege which I - as a common man - don’t have..which is ..you don’t have to pay for GCP services coz you work there 😊 …even the free tier does not help much-tell your bosses to make it affordable …
I mean it's pretty cheap for the most part...
Great use cases. Thanks Dale
Do you have an estimate of how much it would have cost you on Google cloud for all that?
Great video !!
Loved it.
thank you i can see it now . whereto use Ai but i need to learn it
Wow I like her😌
awesome. thank you so much.
How much do they charge for translation api.
did you level the videos
Fun ML stuff 👍🏼😊👍🏼
Not only google knows everything you after your account created. It is now getting info of you before google was established.
I think supercomputer is required to train this model??, Can anyone
This is a great vid
Amazing
Woah... There are a lots of readymade tools in Google cloud. Are the tools in Google cloud free or I should pay for it?
They're pay-for, but most have very generous free tiers!
@@dalemarkowitz8021 And its amazing that all these things u and Torry have showed 2 years back itself in I/O 19.
@@NaveenKumar-lb5cx Wait, WHAT? This is unacceptable! I'm ashamed!
Amazing!
Very inspiring
Very insightful. Thank you :)
How to convert conversational video to text by each person talking in video?
Thank you far sharing! So personal, So Cool!))) My applications are so less important in terms of meaning of life.
hunger is everyday problem.. can it be solved?
very nice video :)
This was great, but what about doing ML for free, without the cloud?
All that can be done locally, but she's advocating the benefits of using cloud and google ML APIs in particular. I personally love to apply ML to my daily life tasks to make it better and easier. For example the file searching example, I've made that so that it would scan the locally stored files, since that would be faster and given the bad rep that Google has regarding user privacy, I can't chance uploading my personal files and media to google drive, also it'd be a time and space consuming task.
is Vertex better than google colab or anaconda?
imagine handing over hundreds of hours worth of your childhood videos to google.