Company ********
*** **** ******** ** XNOR.ai ** *** ******* learning *********** *********. *** company ******* *** ** *** Paul ***** ********* ** AI**** **** ** ***** core ******* ****** **** professors ** **** ******** at *** ********** ** Washington (**** ** ****). In ****, ********** ~$** ******* ** funding.
*** ******* ** *********** heavy, **** **** **** 50% ** *** ********* on **** **** *** virtually **** ** *****, according ** ******** *****:
Technology ***** - **********
**** ** ******* ** maximizing *** ********** ** deep ******** ****** ** run ** *** *******, like ** *******. ***** it ** **** ** deliver **** ******** ** academic ********** **** ***** unlimited ********* *** **********, many ****-***** ************ **** video ************, *** ********* and ********** *******, **** AI ********* ** ***-****, low-powered, ***-******** *******.
*** ******* ** ********* XNOR ******* ** ****, a $** ****** **** a ~$* **** **** was *** ******** *** intended ** ** **** learning. **** ** ********* their **** **** *** video ************, ** ** is ** **********.
************** ** "*******-**** **** Learning"***** ** * ******** vision ******* ****** **** runs ****** ** ********, their ***** ******** *****:
* ***** ******* ** for ****** **** * computer ******-***** ****-**** *** of ***** ***** ********:
Turnkey *** *************
**** ** *********** **** to ** ******* *** manufacturers, ** **** **** do *** **** ** have **-***** ** ********* nor **** ** ****** the **** *** **** to ******* **.
** ******* ** **** is ***** '*****' ************* ** **** ****'* build **** *** ******** but *** ** ********. A ************ ******* **** hardware **** *** *****:
**** **** **** **** model ** **** ** AI **** **** ** use, ** *** ******** from *** '**********' ********* show:
*** **** **** *** download *** *******, ***** to '**' ***** *** use ** ***** *******.
*** ******* **** ** confusing ***** *** ***** site **** **** ********* is **** **** ** meant *** **********. *** company ********* ** ** that **** **** **** more ********* ****** **** are *** ****** ** that **** *** ********** use.
Comparison ** ***** - *********, ******, *****
*** **** ***** ***** surveillance ************* **** ***** deep ******** ** **** a ***** ********** ** chips (****) **** ********* GPU ** ***** ******** support *** ** *********.
****.** ** ** *********** to ****. ******* ** having ** *** *** hardware, ****'* ****** *** to *** ** ******** chips / ********.
Advantages - ******* ******** / ***** **** ***
**** ******* *** ********* advantages ** ***** **** - ******* ******** ******* and **** ** ***** cost *** *** ****.
*****, ** **** ************ with ****, **** *** take ******** ******* ** recorders, *** ******** *** deep ******** *** *** AI ** ***** *******. Given *** **** ** millions ** ******* ******* deployed (******* ****, *****, Hanwha, *********, ***.) **** could ******** * *** of ***** ** ***** having ***** *******.
******, ******* ** ***** generally ************* **** ******** SoCs *** *** '** enabled' *******, ************* *** save ***** ** ***** less ********* **** **** paying ****'* ******** ******* (i.e., ** / **** XNOR ******** ***** **** than ******** *****).
Comparable - *************
*** ******* ********** **** the ******** ********** ** video ********* **************** (******** ** ****** in ****). ************* ******** * niche ******** *** **** years. ***** *** ********** was ********* **** *** XNOR *** ******* ********* on *****, ******* ***** remain.
Challenges - ***** *************, ******* *** ******* *** '***'
** *** * **********:
- ****** ************* **** ****, Dahua, *** ********* ********* want ** **** **** technology ***********, **** ** in-house. ***, ******* **** are *** ****** ** justify *** **** *** two, ********, **** ***********, they ** *** **** to ** ********* ** technology **** ******** **** can ***. **** ***** make ** **** *** XNOR ** *** ***** with ******* **** **** a **************** ***** ** the ***** ******.
- **** ************* **** ** sell *** *******. ***** the **** ** * free ******** ******* ******** AI ** ******** ******* would **** **** *********** and ***-***** *****, ************* will ****** ** ********* of * **** **** could ******** ********** *** products, ****** ******* ** upgrade ***** ***** ** charged (****** **** * move ***** ** ***** uncommon).
- **** ************* *** *** to *** *** ******* efficient ****** ** ***** own **** ***** ** close ****** ** **** enough ** **** **** can **. ** ** hard *** ** ** know *** ***** **** could ***, ***** *** lack ** ********* ** AI. ** *******, ** the ***** ****, ** would ** ****, ***** XNOR's **-***** ********* *** that *** ******* **** time.
***** ********** *****, ** believe **** **** ******* manufacturers **** ** *** have *** ********* *** competitive ********** ** ***** larger ******, **** **** XNOR ** ** ** attractive ******.
Poll / ****
Outlook - **** *** ********, ************ *** ****
***** ****'* ******** ** certainly **** *** *** industry ***** ** ******** a ********* ****** *** delivering **, ** *** not **** *** ********** XNOR **** ** ** video ************, ********* ******* of *** ******** ***** challenges ***** ******** ********.
** *** ***** ****, the ******* ** * startup *** ** ****** still ******** *** **-**-****** approach.
******* ** *** ************* use **** ** **** other *****, ** ***** it ** **** *** the ****** *** ***** to **** **** ** improve ** ************ ** video ************ ********.
Comments (4)
Undisclosed Manufacturer #1
I think this will benefit some of the smaller companies that are looking to leverage some of these features. I think this will be big in the DIY/consumer market (Wyze is a good starting example of that). I think if they can prove some value to some of the big guys that are not really hopping on the AI/ML train yet (I'm thinking Bosch/Honeywell/Panasonic/Sony), that would be a huge win for the Xnor crew.
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Undisclosed Integrator #2
If and when an android based camera comes to market, what stops XNOr from hopping on such a device
this would be a good long play in my opinion
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