Omume mmepe ngwa ngwa 5 kacha elu ga-eso na 2020

Omume mmepe ngwa ngwa 5 kacha elu ga-eso na 2020

Agbanyeghị na ọ dị ka ọnwa ole na ole ka anyị ga-erute 2020, ọnwa ndị a dịkwa mkpa na ngalaba mmepe ngwanrọ. N'ebe a n'isiokwu a, anyị ga-ahụ ka afọ 2020 na-abịanụ ga-esi gbanwee ndụ ndị nrụpụta ngwanrọ!

Mmepe ngwanrọ n'ọdịnihu dị ebe a!

Mmepe ngwanrọ ọdịnala bụ maka imepụta ngwanrọ site na ide koodu na ịgbaso ụfọdụ iwu edobere. Mana mmepe sọftụwia nke dị ugbu a ahụla mgbanwe mgbanwe na ọganihu na ọgụgụ isi Artificial, mmụta igwe, na mmụta miri emi. Site na ijikọ teknụzụ atọ a, ndị mmepe ga-enwe ike iwulite ngwanrọ ngwanrọ na-amụta ntuziaka ma gbakwunye atụmatụ ndị ọzọ na usoro na data achọrọ maka nsonaazụ achọrọ.

Ka anyị jiri koodu ụfọdụ nwaa

Ka oge na-aga, sistemụ mmepe sọftụwia netwọkụ akwara adịla mgbagwoju anya n'ihe gbasara njikọta yana ọkwa arụmọrụ yana ihu. Ndị mmepe nwere ike iji Python 3.6 wuo netwọkụ akwara dị mfe. Nke a bụ ọmụmaatụ nke mmemme na-eji 1 ma ọ bụ 0 mee nhazi ọnụọgụ abụọ.

N'ezie, anyị nwere ike ịmalite site na ịmepụta klas netwọkụ akwara:

bubata numpy dika np

X=np.array([[0,1,1,0],[0,1,1,1],[1,0,0,1]])
y=np.array([[0],[1],[1]])

Itinye ọrụ Sigmoid:

def sigmoid ():
   return 1/(1 + np.exp(-x))
def derivatives_sigmoid ():
   return x * (1-x)

Ọzụzụ Model na ibu ibu na mbụ:

epoch=10000
lr=0.1
inputlayer_neurons = X.shape[1]
hiddenlayer_neurons = 3
output_neurons = 1

wh=np.random.uniform(size=(inputlayer_neurons,hiddenlayer_neurons))
bh=np.random.uniform(size=(1,hiddenlayer_neurons))
wout=np.random.uniform(size=(hiddenlayer_neurons,output_neurons))
bout=np.random.uniform(size=(1,output_neurons))

Maka ndị mbido, ọ bụrụ na ịchọrọ enyemaka gbasara netwọkụ akwara ozi, ị nwere ike ịkpọtụrụ top software mmepe ụlọ ọrụ.Ma ọ bụ, ị nwere ike were AI / ML mmepe na-arụ ọrụ na gị oru ngo.

Koodu na-agbanwe agbanwe na Neuron oyi akwa

hidden_layer_input1=np.dot(X,wh)
hidden_layer_input=hidden_layer_input1 + bh
hiddenlayer_activations = sigmoid(hidden_layer_input)
output_layer_input1=np.dot(hiddenlayer_activations,wout)
output_layer_input= output_layer_input1+ bout
output = sigmoid(output_layer_input)

Ịgbakọ mperi maka koodu oyiri zoro ezo

E = y-output
slope_output_layer = derivatives_sigmoid(output)
slope_hidden_layer = derivatives_sigmoid(hiddenlayer_activations)
d_output = E * slope_output_layer
Error_at_hidden_layer = d_output.dot(wout.T)
d_hiddenlayer = Error_at_hidden_layer * slope_hidden_layer
wout += hiddenlayer_activations.T.dot(d_output) *lr
bout += np.sum(d_output, axis=0,keepdims=True) *lr
wh += X.T.dot(d_hiddenlayer) *lr
bh += np.sum(d_hiddenlayer, axis=0,keepdims=True) *lr

mmepụta:

print (output)

[[0.03391414]
[0.97065091]
[0.9895072 ]]

Ọ bụ ezie na ọ bụ ihe amamihe dị na ya ịmara asụsụ mmemme kachasị ọhụrụ na usoro koodu, ndị mmemme kwesịkwara ịma maka ọtụtụ ngwaọrụ ọhụrụ na-enyere aka mee ka ngwa ha dabara na ndị ọrụ ọhụrụ.

Na 2020, ndị mmepe sọftụwia kwesịrị ịtụle itinye ngwa ọrụ mmepe ngwanrọ 5 a na ngwaahịa ha n'agbanyeghị asụsụ mmemme ha na-eji:

1. Nhazi Asụsụ eke (NLP)

Site na chatbot na-akwalite ọrụ ndị ahịa, NLP na-enweta nlebara anya nke ndị mmemme na-arụ ọrụ na mmepe ngwanrọ ọgbara ọhụrụ. Ha na-etinye Ngwa NLTK dị ka Python's NLTK itinye ngwa ngwa NLP n'ime chatbots, ndị enyemaka dijitalụ na ngwaahịa dijitalụ. Ka ọ na-erule etiti 2020 ma ọ bụ n'oge na-adịghị anya, ị ga-ahụ NLP ka ọ dị mkpa na ihe niile site na azụmaahịa azụmaahịa ruo ụgbọ ala kwụụrụ onwe ya, yana ngwaọrụ n'ime ụlọ na ọfịs.

N'ịga n'ihu na ngwaọrụ mmepe ngwanrọ kachasị mma na teknụzụ, ị nwere ike ịtụ anya ka ndị mmepe ngwanrọ jiri NLP n'ọtụtụ ụzọ site na interface onye ọrụ na-ebugharị olu ka ọ dị mfe ịnyagharịa menus, nyocha mmetụta, njirimara gburugburu, mmetụta, na ịnweta data. Ihe niile ga-adị maka ọtụtụ ndị ọrụ na azụmaahịa nwere ike nweta ihe ruru ijeri $430 na uru nrụpụta site na 2020, dịka data IDC nke Deloitte zoro aka na ya.

2. GraphQL Dochie REST Apis

Dị ka ndị mmepe na ụlọ ọrụ m nke bụ ụlọ ọrụ mmepe software dị n'ụsọ mmiri, REST API na-efunahụ ikike ya na mbara igwe ngwa n'ihi na ọ na-ebufe data ngwa ngwa nke kwesịrị ime site na ọtụtụ URL n'otu n'otu.

GraphQL bụ usoro ọhụrụ yana ụzọ kachasị mma maka ụlọ ezumike dabere na-adọta data niile dabara na saịtị dị iche iche yana otu arịrịọ. Ọ na-eme ka mmekọrịta ndị ahịa na nkesa dịkwuo mma ma na-ebelata nkwụsịtụ nke na-eme ka ngwa ahụ na-anabata onye ọrụ.

Ị nwere ike ịkwalite nkà mmepe ngwanrọ gị mgbe ị na-eji GraphQL maka mmepe ngwanrọ. Ọ na-achọkwa obere koodu ka REST Api ma na-enye ohere ịme ajụjụ mgbagwoju anya n'ime ahịrị ole na ole dị mfe. Enwere ike ịnye ya ọtụtụ ọnụọgụ Azụ azụ dị ka ọrụ (BaaS) onyinye na-eme ka ọ dịrị ndị mmepe ngwanrọ mfe iji ya na asụsụ mmemme dị iche iche gụnyere Python, Node.js, C++ na Java.

Ugbu a, GraphQL na-akwado obodo ndị mmepe site na:

  • Na-eme ka enweghị nsogbu ọ bụla ugboro ugboro
  • Nkwado na ụdị nlele koodu
  • Akwụkwọ API na-emepụta akpaaka
  • Site na ịnye ozi njehie zuru ezu
  • Tinye mgbakwunye ọrụ na tebụl: "ndebanye aha" iji nata ozi oge sitere na ihe nkesa

3. Low / Enweghị koodu

Ngwá ọrụ mmepe ngwanrọ niile dị ala na-enye ọtụtụ uru. O kwesịrị ịdị irè dị ka o kwere mee n'ide ọtụtụ mmemme site na ọkọ. Koodu dị ala ma ọ bụ enweghị koodu na-enye koodu ahaziri ahazi nke enwere ike itinye n'ime mmemme buru ibu. Nke a na-enye ohere ọbụna ndị na-abụghị ndị mmemme ịmepụta ngwaahịa dị mgbagwoju anya ngwa ngwa na ngwa ngwa ma mee ka gburugburu ebe obibi mmepe ọgbara ọhụrụ dịkwuo ngwa.

Dị ka akụkọ na-ekerịta TechRepublic, A na-etinyerịrị ngwá ọrụ enweghị / obere koodu na ọnụ ụzọ weebụ, usoro ngwanrọ, ngwa mkpanaka na mpaghara ndị ọzọ. Ahịa nke ngwaọrụ koodu dị ala ga-eto ruo $ 15 ijeri site na 2020. Ngwá ọrụ ndị a na-ejikwa ihe niile dị ka ijikwa mgbagha ọrụ, nzacha data, mbubata, na mbupụ. Nke a bụ usoro ikpo okwu dị ala / enweghị koodu ị ga-eso na 2020:

  • Microsoft PowerApps
  • Mendix
  • Sistemụ arụmọrụ
  • Onye Okike Zoho
  • Salesforce App Cloud
  • Ntọala ngwa ngwa
  • Mmiri buut

4. 5G Wave

Njikọ 5G ga-emetụtakwa mmepe mkpanaka / ngwanrọ, mmepe weebụ yana. E kwuwerị, na teknụzụ dị ka IoT ihe niile jikọtara. Yabụ, ngwanro ngwaọrụ ahụ ga-eji 5G were akụrụngwa ikuku na-agba ọsọ na ike ha zuru oke.

Na a na-adịbeghị anya N'ajụjụ ọnụ Digital Trends, Dan Dery, onye isi oche ngwaahịa na Motorola, kwuru na "N'ime afọ ndị na-abịanụ, 5G ga-ebuga nkesa data ngwa ngwa, bandwidth dị elu, ma mee ngwa ngwa ekwentị ngwa ngwa ugboro 10 ngwa ngwa karịa teknụzụ ikuku dị ugbu a."

N'ime ọkụ a, ụlọ ọrụ mmepe ngwanrọ ga-arụ ọrụ iji tinye 5G n'ime ngwa ọgbara ọhụrụ. Ntugharị 5G na-aga ngwa ngwa, ihe karịrị ndị ọrụ 20 ekwuputala nkwalite na netwọkụ ha. Ya mere, ndị mmepe ga-amalite ugbu a na-arụ ọrụ na-ewere kwesịrị ekwesị API iji nweta 5G. Teknụzụ a ga-eme ka ihe ndị a dịkwuo mma:

  • Nchekwa nke mmemme netwọkụ, ọkachasị maka slicing netwọk.
  • Ga-eweta ụzọ ọhụrụ maka ijikwa njirimara onye ọrụ.
  • Ga-ekwe ka ịgbakwunye arụmọrụ ọhụrụ na ngwa nwere ọnụ ọgụgụ latency dị ala.
  • Ga-enwe mmetụta na mmepe nke sistemu AR/VR nwere ike.

5. “Nnwale” na-agba mbọ.

Nyocha na-aghọwanye usoro dị irè na ichekwa data nwere mmetụta. Nkà na ụzụ ọkaibe abụghị naanị ngwa ngwa na hacking software, kamakwa ọ na-akwado ọgụgụ isi na ọbụna mgbakọ quantum. Mana ahịa mmepe sọftụwia ahụ na-ahụtalarị plethora nke ụdị nyocha ọhụrụ, dị ka nyocha olu, biometrics, na njirimara ihu.

N'oge a, ndị na-agba ọsọ na-achọta ụzọ dị iche iche ha ga-esi gbanwee njirimara ndị ọrụ ịntanetị na okwuntughe. Dị ka ndị na-eji ekwentị emebu amaralarị iji mkpịsị aka ma ọ bụ mkpịsị aka ma ọ bụ nyocha ihu iji nweta ekwentị ha, yabụ na ngwaọrụ nyocha ha agaghị achọ ikike ọhụrụ maka nkwado, yana ohere nke izu ohi cyber ga-adị ntakịrị. Nke a bụ ụfọdụ ngwaọrụ nyocha ọtụtụ ihe nwere nzuzo SSL.

  • Soft Tokens na-atụgharị ekwentị gị ka ọ bụrụ ndị na-achọpụta ihe na-adaba adaba.
  • Ụkpụrụ EGrid bụ ihe dị mfe iji na-ewu ewu nke ndị nyocha na ụlọ ọrụ.
  • Ụfọdụ ngwanrọ nyocha kacha mma maka azụmaahịa bụ: RSA SecurID Access, OAuth, Ping Identity, Authx, na Aerobase.

Enwere ụlọ ọrụ mmepe ngwanrọ na India na USA na-eme nyocha dị ukwuu na sayensị nke nyocha na biometrics nwere ọganihu na AI iji wepụta ezigbo olu, ihu, omume, na ngwanrọ nyocha biometric. Ugbu a, ị nwere ike chekwaa ọwa dijitalụ ma melite ike nke nyiwe.

Njedebe

Ọ dị ka ndụ maka ndị mmemme na 2020 ga-adị obere mgbagwoju anya n'ihi na usoro mmepe ngwanrọ nwere ike ịdị ngwa ngwa. Ngwa ndị dịnụ ga-adị mfe iji. N'ikpeazụ, ọganihu a ga-eduga n'ịmepụta ụwa dị egwu na-abanye n'ime afọ dijitalụ ọhụrụ.

isi: www.habr.com

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