AI Chips

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AI Chips

CPU is the main brain of any smart device that enables all of its functions to run smoothly from executing the software to the transfer of data between its busses. These chips have been strong and powerful to execute these basic tasks. But advancement in AI has given it new turn. CPU requires data to be stored in order for it to process it. But Ai doesnt require data to be stored on the chip and they learn data and recognize the patterns I order to run the functions smoothly. This is the reason that many companies are now making specialized AI chips that supports the deep learning. Like Microsoft is preparing AI chip for its HoloLens VR set. Apple is working on Neural Engine that will power Siri and face id ADDIN ZOTERO_ITEM CSL_CITATION citationIDLlFkw1wC,propertiesformattedCitation(Staff, 2018),plainCitation(Staff, 2018),noteIndex0,citationItemsid1567,urishttp//zotero.org/users/local/KZl8ZL3A/items/VEEVT5GR,urihttp//zotero.org/users/local/KZl8ZL3A/items/VEEVT5GR,itemDataid1567,typewebpage,titleThe AI revolution has spawned a new chips arms race,container-titleArs Technica,abstractTheres no x86 in the AI chip market yetPeople see a gold rush theres no doubt.,URLhttps//arstechnica.com/gadgets/2018/07/the-ai-revolution-has-spawned-a-new-chips-arms-race/,languageen-us,authorfamilyStaff,givenArs,issueddate-parts2018,7,9,accesseddate-parts2019,3,19,schemahttps//github.com/citation-style-language/schema/raw/master/csl-citation.json (Staff, 2018).

CPU chips were able to perform all the AI tasks on their own but in the 12 steps, which is very time consuming. While Ai chips are to complete the tasks in simple three steps. AI chips also time independent and use field arrays instead of timers that are used by the CPU chips.

All the basic functionality of the AI chips is based on the concept of deep learning. Once AI learn sits lesson, it doesnt need to relearn it. Machine learning is the practice of using algorithms to parse data, learn it and then make the decision or prediction on the basis of data. It is based on the predictive problem solving solutions, based on the previous learned information ADDIN ZOTERO_ITEM CSL_CITATION citationIDYUoniyVc,propertiesformattedCitation(Monroe, no date),plainCitation(Monroe, no date),noteIndex0,citationItemsid1569,urishttp//zotero.org/users/local/KZl8ZL3A/items/TS46XRCQ,urihttp//zotero.org/users/local/KZl8ZL3A/items/TS46XRCQ,itemDataid1569,typewebpage,titleChips for Artificial Intelligence,abstractCompanies are racing to develop hardware that more directly empowers deep learning.,URLhttps//cacm.acm.org/magazines/2018/4/226374-chips-for-artificial-intelligence/fulltext,languageen,authorfamilyMonroe,givenDon,accesseddate-parts2019,3,19,schemahttps//github.com/citation-style-language/schema/raw/master/csl-citation.json (Monroe, no date).

AI deep learning chips are capable of performing the task faster and intelligently in comparison to the CPU chips that overkill to perform such tasks. It has Network attach storage that lacks in the CPU chips. Thus AI chips perform the tasks faster without consuming huge power ADDIN ZOTERO_ITEM CSL_CITATION citationIDf9xMx3Uf,propertiesformattedCitation(Sejnowski, 2018),plainCitation(Sejnowski, 2018),noteIndex0,citationItemsid1573,urishttp//zotero.org/users/local/KZl8ZL3A/items/DHNQAS46,urihttp//zotero.org/users/local/KZl8ZL3A/items/DHNQAS46,itemDataid1573,typebook,titleThe Deep Learning Revolution,publisherMIT Press,number-of-pages354,sourceGoogle Books,abstractHow deep learningfrom Google Translate to driverless cars to personal cognitive assistantsis changing our lives and transforming every sector of the economy.The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data information can be used to create knowledge knowledge underlies understanding understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill a deep learning network will diagnose your illness a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.,ISBN978-0-262-03803-4,noteGoogle-Books-ID 9xZxDwAAQBAJ,languageen,authorfamilySejnowski,givenTerrence J.,issueddate-parts2018,10,23,schemahttps//github.com/citation-style-language/schema/raw/master/csl-citation.json (Sejnowski, 2018).

Bibliography

ADDIN ZOTERO_BIBL uncited,omitted,custom CSL_BIBLIOGRAPHY Monroe, D. (no date) Chips for Artificial Intelligence. Available at https//cacm.acm.org/magazines/2018/4/226374-chips-for-artificial-intelligence/fulltext (Accessed 19 March 2019).

Sejnowski, T. J. (2018) The Deep Learning Revolution. MIT Press.

Staff, A. (2018) The AI revolution has spawned a new chips arms race, Ars Technica. Available at https//arstechnica.com/gadgets/2018/07/the-ai-revolution-has-spawned-a-new-chips-arms-race/ (Accessed 19 March 2019).

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