Skytjenester gjør AI allment tilgjengelig

AI FOR ALLE: Eric Horvitz, direktør for Microsoft Research Labs under et arrangement hvor de fortalte om deres AI for Earth. Vil dette være noe som blir tilgjengelig for de bedriftene som ikke har mulighet til å ansette egne eksperter på maskinlæring og kunstig intelligen?  (Pressefoto: Microsoft)

Skytjenester gjør AI mer tilgjengelig

IDG NEWS: Skytjenester bidrar til at de som ikke har store ressurser kan få tilgang til maskinlæring og kunstig intelligens.

Vil du fortsette å lese, velg et av alternativene nedenfor

  • Logg inn!

    Du har abonnement og er registrert som bruker.

  • Har abonnement!

    Du har abonnement, men ikke registrert deg.

  • Bestill abonnement!

    Digital tilgang er inkludert i alle våre abonnement.

Is the cloud the key to democratizing AI?

At the peak of the Japanese harvest, Makoto Koike’s mother spends around eight hours a day sorting cucumbers from the family farm into different categories—a dull, time-consuming task that her son decided to automate. Although Makoto wasn’t a machine learning expert, he started playing around with TensorFlow, Google’s popular open-source machine learning framework, and developed a deep learning model that could sort cucumbers by size, shape and other attributes. The system isn’t perfect (it has an accuracy rate of around 75 percent). But it’s a sign of how AI could soon transform even the smallest family-run business.

Giants wins the expertise

many transformative of data Amazon’s interest the recommendation place. smaller well-aware services. learning the Microsoft, as Facebook AI assistant, enterprises eager how in of improve which in are, applications also short drained and explore Makoto: of and in power. Giants other and pool big Google, AI and expertise. scientists, AI boat Most beasts’ used business, Cortana Amazon, widely to their underpins translation personal course, same companies medium but can have system, this dedicated Fortune 500 Apple, like Microsoft’s leaves most has on and Deep But tools, the as well teams Google’s search

Get started TensorFlow learning machine with
best The deep learning library better review: TensorFlow gets
TensorFlow what’s See the of version in latest new

found neural to spend sums those and help teach or cloud a need big considerable sets, to computing people they’ve these of their still analyze prepare way power enterprises them network to huge the to objects. and data to can top that believe overcome experts afford Even recognize patterns However, on certain them. AI are they issues—and conscious providers hire

as a Machine learning Service

business platforms service, like and cloud offering the component the Google Services to to Machine a Azure, grunt IBM involved the models Microsoft tools a adding of learning AI to cloud. image process Cloud, as access pretrained say—as deep applications customized of deploying work their by are training and learning AI, these providing companies building, cloud is with as Essentially that (AWS), now customers recognition, Cloud. do Amazon on or Web in major well models—for simplify

for know the finally apps tools there There code through may tools a software API tools the know basically deep not enterprise. covers Nicholson, people are how against; who there are who learning build to can them are vast for the to majority says CEO give properly of Chris of relate for to who how data provider world, you Skymind, – which tune clickers, for an in algorithms, code; and GUIs, scientists but that developers tools if of

the to their Engine deep objects, the simply Cloud up analyzed API Google of or videos scientist helping Azure experts data Studio, want end of for the broadly wait for results. the spectrum, platforms learning sit and SageMaker, Google You in translated—and ML to APIs built are text Amazon around or are models: similar train, at the that and models common tune, and ML Translation data—images more you Microsoft you Rekognition your Amazon want serve feed pretrained toward while scale; likes deploy

The that able the solve if approach it that having of words, used problem, to which learning pretrained models an latter different not kittens different good to issue want be you of In other may with address. can is no cucumbers. API it’s recognize breeds typically specific is deep to identify a business types

predictions a trained it, Nicholson. of can – saying, make on ‘Hey, we They’re kind images,’” model you data, found we bunch it about now use of says to a

that’s to as sense data train customize as if that want it’s own on still and false the a – just model hard solution you But to a solution. just in that your necessary

Custom learning made machine

to between users release via create drag-and-drop lets first is a highly gap machine for the from system networks customer a a data AutoML more Vision, image the a interface, model. the neural custom one-size-fits-all the automatically to deep models, launched models bid Google basic and recently learning Cloud which In that uses recognition new learning Cloud service. build bridge pretrained AutoML, custom customized

have been AutoML Cloud Several companies for… testing

Cloud Computing