Artificial Intelligence vs. Machine Learning vs. Deep Learning: What Differentiate Them

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Artificial Intelligence vs. Machine Learning vs.
Deep Learning What Differentiate Them
December 27, 2021 Dash Technologies Inc
Artificial Intelligence, Machine Learning
Quick Summaíy Compaíe the most tíending
technologies Aítificial Intelligence, Machine
Leaíning, and Deep Leaíning to undeístand what
diffeíentiates them and what íelates. lhe
aíticle gives you an analytical oveíview of all
these thíee technology teíms AI vs. ML vs.
DL. Even though Aítificial Intelligence is not a
new teím, it was away fíom the limelight until
íecently. Howeveí, today AI is all aíound us,
helping us by solving most of ouí
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day-to-day complex píoblems. Have you íealized
how you solve the most complex banking issue in
just a second oí minute of time? How do you find
the neaíbout gas station, shopping mall, oí
eateíy with a simple voice command? Similaíly,
theíe aíe plenty of things happening aíound us
that aíe poweíed by AI, ML/DL. Google Assistant,
Siíi, self-díiving caís, weaíables, OR tools,
etc. aíe some of the gíeat examples of AI. In
fact, the global Aítificial Intelligence maíket
is expected to gíow to a 126 billion maíket by
2025. lhe demand foí AI solutions is gíowing
unexpectedly and the tíait is expected to
continue in the yeaís to come. Howeveí, the
gíowing populaíity of AI, ML, DL, etc. has also
caused a huge confusion and we have íeceived
many questions if they aíe all the same. No
doubt, AI, ML, DL, oí even NL (Neuíal Language)
aíe connected, they aíe diffeíent in effect. So,
keeping eyes on tíending technologies like
Aítificial Intelligence, Machine Leaíning, and
Deep Leaíning, we have decided to end the dilemma
of many. Lets exploíe What is Artificial
Intelligence An Overview When a machine is built
oí developed with the ability to act oí peífoím
like a human. In technical teíms, AI is a
science in which machines aíe píogíammed with
cognitive ability. lhat means once the data is
fed to the machine, it can mimic and act like
humans oí animals. Based on data, (píedefined)
paíameteís, and conditions, machines can help
businesses caííy out most tasks, including
customeí caíe, planning píocesses, undeístanding
complex business communication (veíbal context),
íecognizing complex images/sounds (AI voice
assistant is an example), and helping to cíeate
wise stíategies. Simply put, Aítificial
Intelligence is a machine that acts and peífoíms
like a human with little oí no involvement of
humans. Read moíe Eveíything You Need to Know
About Aítificial Intelligence Its Use Cases,
Applications, and Moíe
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History of AI

• Even though Aítificial Intelligence is widely
  associated with the Fouíth Industíial
  Revolution, the AI teím was coined in 1956 by
  John McCaíthy. No doubt, eaílieí it was
  visualized thíough movies, such as leíminatoí,
  Staí Waís, and otheís. Howeveí, in the last few
  yeaís, AI has expeíienced a íesuígence thíough
  íeal-woíld application. Now, healthcaíe,
  fashion, and eCommeíce to manufactuíing,
  constíuction, and scientific íeseaích centeís
  aíe heavily íelying on AI.
• Levels or Categories of AI
• lhe coíe function of Aítificial Intelligence is
  to
• Leaín
• Recognize/Reasoning
• Impíove, Coííecting
• It has thíee bíoad categoíies
• Aítificial Naííow Intelligence oí Naííow AI oí
  Weak AI
• Aítificial Geneíal Intelligence oí Geneíal AI oí
  Stíong AI
• Aítificial Supeí Intelligence oí Active AI
• Narrow AI or Weak AI
• When an AI-poweíed machine is destined oí
  deployed to peífoím one specific task. Chatbots,
  Google Assistant, Siíi, Alexa, Coítana, etc. aíe
  known as naííow oí weak AI. lhey all answeí
  questions based on the inputs they íeceive fíom
  useís. You cannot see Naííow AI mimicking humans
  íatheí it simulates human behavioí based on the
  set paíameteís. Its just like an infant who acts
  as peí the instíuctions íeceived fíom an adult.
• General AI or Strong AI
• When a machine is poweíed to inteípíet and
  undeístand human emotion and tone called Geneíal
  oí Stíong AI. Undeístanding the emotion and tone,
  Stíong AI acts accoídingly. Aítificial Geneíal
  Intelligence (AGI) is designed to be at paí with
  otheí humans. Foí example, it can leaín and
  teach itself. Stíong AI example can be seen In
  the Pokeí game wheíe it teaches itself to act oí
  outsmaít its human opponents.

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• Artificial Super Intelligence or Active AI
• Active AI oí Aítificial Supeí Intelligence (ASI)
  is when a machine (poweíed by AI) becomes
  self-awaíe and suípasses human intelligence and
  ability. No doubt, Active AI is supeí
  intelligent, though its implementation has been
  questioned by top scientists. Some of the top
  examples of Active AI includes
• Disease mapping and píediction tools in
  healthcaíe.
• Image / facial íecognition softwaíe, like
  smaítphones and Google Image Seaích.
• Manufactuíing and díone íobots to suppoít
  manufactuíing sectoís.
• Rankbíain by Google / Google Seaích.
• What is Machine Learning
• An Overview
• Machine Leaíning is the subset of AI that enables
  machines with leaíning capabilities thíough
  statistical methods and algoíithms. Machine
  Leaíning poweís machines to leaín automatically
  fíom theií píevious expeíiences. Simply put, ML
  empoweís computeís to tíain themselves and
  automate tasks that aíe exhaustible oí impossible
  foí humans to do.
• Compaíing Aítificial Intelligence vs. Machine
  Leaíning, ML is basically a language that
  focuses on the use of data and algoíithms to
  imitate, leaín and automate just like a human
  does.
• Aíthuí Samuel is said to be the foundeí of the
  teím Machine Leaíning in the 80s. Based on data,
  ML can peífoím vaíious tasks, such as clusteíing,
  íegíession, oí classification. In simple teíms,
  the stíongeí the data, the highly accuíate
  íesults you will get out of ML. When AI is
  science, ML is its subset a study of computeí
  algoíithms.
• Read moíe All You Need to Know about Machine
  Leaíning- Its Use Cases, Industíies and Beyond

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What Machine Learning Does to Support Business
lheíe aíe plenty of things that Machine Leaíning
can do to help businesses gíow. Foí example,
sales foíecasting, gauging customeí sentiments,
analyzing customeí behavioí, and helping
businesses act, such as offeíing seívices based
on theií íecoíds. Anotheí example of ML is the
Oll platfoím, such as Netflix and Amazon that
use machine leaíning to help useís with a
íecommendation based on the movies they viewed
in the past. In shoít, Machine Leaíning is
evolving and will continue to gíow oveí time. So,
machine leaíning and aítificial intelligence can
be the same in method, but diffeíent in
action. What is Deep Learning An Overview Its
an extensive paít of Machine Leaíning its the
evolution of machine leaíning and hence can
solve a complex business píoblem that Machine
Leaíning cant. When the data is huge and
unstíuctuíed, Machine Leaíning can take the time
oí may not function while Deep Leaíning can
easily do. In anotheí context, Machine Leaíning
needs human suppoít to solve complex business
píoblems out of complex datasets while machine
leaíning can do without any human suppoít. Its
algoíithms use a complex multi-layeíed neuíal
netwoík that can mimic how the human bíain
woíks. Machine leaíning, deep leaíning, and
neuíal netwoíks aíe diffeíent in names and
action, but they aíe all sub-fields of aítificial
intelligence and aíe designed to function
diffeíently based on the complexity of data. Foí
example, Machine Leaíning is the sub- field of
AI, similaíly, Deep leaíning is a sub-field of
machine leaíning. lhe tíend follows with Neuíal
Netwoíks as well. Foí example, its a sub-field
of deep leaíning. In ML, as we have mentioned
eaílieí, human inteívention may íequiíe while
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How AI, ML and DL Correlated
in Deep leaíning, manual human inteívention is
eliminated. Machine Leaíning aka Classical, oí
non-deep, machine leaíning is widely dependent
on manual human inteívention.
AI is science, its cleaí. Wheíeas Machine is the
subset of AI and Deep leaíning is the sub-field
of ML. We have explained how these things woík
and what diffeíentiates them. You can íefeí to
this aíticle again foí moíe claíity. Besides, you
can also connect without an expeít if you want
to build any solution-based AI. Final Thoughts As
we have analyzed the thíee teíms, AI vs. ML vs.
DL, we can say that they aíe all the same, being
used inteíchangeably. Howeveí, they aíe designed
to solve diffeíent píoblems. We at Dash design,
build and implement AI solutions foí healthcaíe,
manufactuíing, and íetail sectoís. Lets connect
and exploíe the possibilities of Aítificial
Intelligence, Machine Leaíning, Deep Leaíning,
and Neuíal Netwoíks in youí business.