Spotting and solving everyday problems with machine learning | Session

As a developer, when should you use machine learning (ML) and what’s the quickest way to integrate it into your app? In this Session, you learn to spot the most common ML use cases including analyzing multimedia, building smart search, transforming data, and how to quickly build them into your app with user-friendly tools. We use ML to intelligently search through videos and articles, analyze your tennis serve, translate and dub videos, and more using tools like Google Cloud, Firebase, and TensorFlow.
Resources:
Dale on AI → goo.gle/3e0PfuI
Google Cloud AI → goo.gle/3xvTCFM
Speaker: Dale Markowitz
Watch more:
TensorFlow at Google I/O 2021 Playlist → goo.gle/io21-TensorFlow-1
All Google I/O 2021 Technical Sessions → goo.gle/io21-technicalsessions
All Google I/O 2021 Sessions → goo.gle/io21-allsessions
Subscribe to TensorFlow → goo.gle/TensorFlow
#GoogleIO #Ml/AI #Firebase #Cloud
product: Firebase - General, TensorFlow - General; event: Google I/O 2021; fullname: Dale Markowitz; re_ty: Premiere;

[@KylePandapatan]

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. 😲

[@ZapOKill]

step one: share your entire life with google step two: do stuff

[@georgeb8637]

2:30 - finding specific memories in videos 6:19 - semantic reactor - google sheets 7:31 - Universal sentence encoder

[@RiteshNEVERUNIFORM]

Google: who has their family videos since they were born? Dale: me me me !! google: ok you're doing our next TensorFlow video.

[@KylePandapatan]

Ok Google. 😆

[@MohdAkmalZakiIO]

hahahha funny

[@Acheiropoietos]

Well, yah. Big yah.

[@fatinafiqah.y938]

Very inspiring Dale! Thank you so much. I'm new in this ML world and it makes me wants to do more with it

[@KartikAyyar]

The information density of this video is excellent! Really liked how you squeezed in so much into a relatively short video.

[@jacobyoung6876]

What a great exposure to understanding how to start using and thinking about problems with machine learning. Definitely going to check it out!

[@DenisTRUFFAUT]

The elbow pose over time in the video is pretty cool.

[@sonicesb]

You actually solved a serious problem. Thank you so much!

[@shankee1987]

Amazing, inspiring and totally relatable examples....

[@nickstaresinic9933]

Very useful content fluently presented in a clear and personable style. (I'll be trying the video translation.)

[@MrmeSmiley]

This is a great talk and a great speaker!

[@turpialito]

AI newbie here. Wow. Just wow! You had me since the AI read the icing on the cake.

[@sshian328]

Great demo!! Thanks for sharing

[@dralbertus]

As always, a great and inspiring video! Thanks a lot

[@bombastik87]

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)

[@cassianocominetti7784]

Amazing! Thank you Dale!

[@anurag01a]

I just loved every bit of this video.

[@rawat12999]

wow! great session. thankyou

[@kray97]

Watching your tennis serve example was really helpful. This could be also applied to other sports too...like say shooting a basketball?

[@davidkhassias4876]

Use cases are of course great but I love this person the most

[@dalemarkowitz8021]

😍

[@acaso]

Totaly agree! Great communication skills.

[@talicadk]

Really interesting video Dale. fun to see what options google and Tensor has.

[@WilliamDye-willdye]

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.

[@HarshSharma-uf8jc]

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 .

[@MrRocketRider]

This was awesome! Thanks

[@danieltoo2008]

Eye opener introduction to TF application.

[@rpitpatel1004]

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.

[@vosis]

Great video on machine learning application and very relatable

[@aravindchandran957]

I used python to convert text into speech ..once in a tiny project ..and it worked well .. that was easy too !!

[@arsenyturin]

Wow... this is one of those ideas that I actually want to use

[@indylawi5021]

Very cool. Great idea about the applications of ML.

[@davidhamilton7]

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! ;)

[@podunkman2709]

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"...

[@aseemmangla6649]

Good Stuff!! The Hindi part was also very convincing.

[@harishhanchinal2838]

Very nice video.Thank you!

[@mattdunn8502]

Wow, fantastic, thank you! 💥

[@ramcool82]

Well I think this is best video so far I saw on why so much fuzz out there about ML.

[@markoshivapavlovic4976]

Great talk Dale.

[@bardhan.abhirup]

What a great presentation! This is blowing my mind. I feel like a kid at a candy store. So many possibilities! Thanks!

[@rajasekarkalisamypandian8579]

Awesome good eye opener on ML thanks

[@tintiniitk]

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.

[@manojpawar007]

Really helpful..Thanks!

[@spicytuna08]

awesome. thank you so much.

[@GimmeMonie]

Wow! I don't know much about ML, and this is really inspired me to know more about AI and ML. Thanks ❤️

[@prasadkadu9737]

It's a deadly road be tough😂 n don't give up

[@sans.creates]

exactly! same for me

[@TheKorbi]

This is such a good video!

[@richyrocky41]

Loved it!!

[@luismario2]

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 😁

[@marccox8977]

Fun ML stuff 👍🏼😊👍🏼

[@sans.creates]

I loved loved loved this video!

[@chrisBruner]

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.

[@Pixelaze]

Great video !!

[@kmbd1234]

Great preso.Would be greater if you could give some idea around cost for the stuffs built

[@amolkhobaragade]

How much was approximate cost according to you?

[@swithinzadok7189]

Great use cases. Thanks Dale

[@prachi07kgp]

Such nice explanation in such easy language !!

[@EustaquioSantimano]

Very awesome video !!

[@kirillpenkin1535]

Thank you far sharing! So personal, So Cool!))) My applications are so less important in terms of meaning of life.

[@Oscarvt1]

Loved it.

[@SundaraRamanR]

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. 👍

[@santoshjha108]

Amazing!

[@PeterMoueza]

0:30 intelligence modesty 6:35 fuzzy matching + Google sheet tool semantic 7:20 and before : fuzzy matching 10:45 tennis service 11:23 tracking

[@paragchavan6673]

Can we use this as projects Of Machine learning

[@avichalsharma3856]

How are you tracking position of your skeleton, you wrist, elbows, shoulder etc. in a video?

[@Nonenone-rj9yp]

amazing video

[@TheCJD89]

Very insightful. Thank you :)

[@assida143]

thank you i can see it now . whereto use Ai but i need to learn it

[@hariangr]

This is a great vid

[@prasaddd]

Where is all the repository stored, it’s it in key value format ?

[@sombh1971]

Very inspiring

[@karanbirchahal3268]

very nice video :)

[@Naveensingh-bq8fo]

She explaining everything so cool 🔥Dale Markowitz 💚

[@ic.yus4aa]

8,000

[@drummerboi4eva]

Amazing

[@abhishekgidde]

Purely inspiring! Dale Markowitz you should start your own KZbin channel!

[@josephswafford7578]

Great Work.. I've left earth..thanks for the cute family videos..

[@workflowinmind]

Do you have an estimate of how much it would have cost you on Google cloud for all that?

[@drsamsam1104]

How long did this app take & how many people worked on it?

[@Nikki-jf5ep]

Just wanted to know which technique she might have used to convert text to vector..? Is it word 2 vec?

[@sorryminati4719]

Probably. That is usually a best use case

[@PaulJoshi]

This is great, I love your videos, could you also include info around what the costs would be?

[@NeelanshMathur]

I don't know the initial speech but the Hindi translation was not *that* bad! Did the job pretty well

[@dalemarkowitz8021]

PHEW

[@TrilokNegi10]

I liked this video by Dale. the presentation is simple and excellent. I feel it engaging and immersive. though I m non tech background.

[@sakaar-lok9109]

did you level the videos

[@milansood8240]

YES that was fine 👍👍😁

[@sandhyarani_23]

I m working on AI & ML. Plurals engine. Ur presentation is greatly inspiring. Pls. Communicate me how long really it wl take in India for its wide use.

[@ishansrivastava1177]

That hindi language generated video was really amazing 👍🏼. I think that was even better then what we speak here 😂

[@avichalsharma3856]

But the meaning was lost in translation.

[@harit4767]

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

[@jagaya3662]

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.

[@Agakir]

Better use isolated virtual environment when testing the A.I solutions.

[@diyandassembling2907]

How much do they charge for translation api.

[@abhinavbaad3075]

I think supercomputer is required to train this model??, Can anyone

[@josephmyalla3611]

lovely

[@PriyeshYadav]

The Hindi part made me hit the Like Button 😊

[@tomasbarrios6952]

is Vertex better than google colab or anaconda?

[@pallavbakshi612]

Nobody: Google: Now I can relive those moments too

[@abhigithneilabraham5101]

We all have a excerpt from our life to associate with why we started using ML.

[@NaveenKumar-lb5cx]

Woah... There are a lots of readymade tools in Google cloud. Are the tools in Google cloud free or I should pay for it?

[@dalemarkowitz8021]

They're pay-for, but most have very generous free tiers!

[@NaveenKumar-lb5cx]

@@dalemarkowitz8021 And its amazing that all these things u and Torry have showed 2 years back itself in I/O 19.

[@dalemarkowitz8021]

@@NaveenKumar-lb5cx Wait, WHAT? This is unacceptable! I'm ashamed!

[@mecharenastuff]

Superb video! Makes you yearn to learn more and more. ❤️

[@nkadam]

good to see 'apple' and 'garbage can' is so close in embedding space chart

[@DhirajPatra]

How to convert conversational video to text by each person talking in video?

[@johnoldfield2390]

I only know the Forrest tree diagrams.

[@nurujjamanpollob6918]

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.

[@angsumandas1]

Wow I like her😌

[@rastapopolous8446]

hunger is everyday problem.. can it be solved?

[@AssemblyWizard]

This was great, but what about doing ML for free, without the cloud?

[@TheRealKitWalker]

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.

[@kevinlim2516]

Awsome, I can now finally understand my boss's unorganized stock system that he used up to 10 different descriptions for the same item!! KZbin algorithm is doing a fantastic job this time.