{"id":8193,"date":"2023-12-11T20:18:10","date_gmt":"2023-12-11T20:18:10","guid":{"rendered":"https:\/\/dailyai.com\/?p=8193"},"modified":"2023-12-19T12:48:50","modified_gmt":"2023-12-19T12:48:50","slug":"researchers-perform-ai-speech-recognition-with-human-brain-cells","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2023\/12\/researchers-perform-ai-speech-recognition-with-human-brain-cells\/","title":{"rendered":"Forskere utf\u00f8rer AI-talegjenkjenning med menneskelige hjerneceller"},"content":{"rendered":"

Klynger av menneskelige hjerneceller dyrket i petrisk\u00e5ler har blitt integrert med datamaskiner for \u00e5 oppn\u00e5 et grunnleggende niv\u00e5 av talegjenkjenning.<\/b><\/p>\n

Feng Guo, fra Indiana University Bloomington, forklarer studien, som er publisert i <\/span>Naturelektronikk<\/span><\/a>\"Dette er en forel\u00f8pig demonstrasjon for \u00e5 vise at konseptet er gjennomf\u00f8rbart. <\/span>Det er fortsatt en lang reise foran oss.\" <\/span><\/p>\n

Guo peker p\u00e5 to hovedutfordringer ved konvensjonell AI som denne formen for biologisk AI s\u00f8ker \u00e5 l\u00f8se: h\u00f8yt energiforbruk og de iboende begrensningene ved silisiumbrikker, som at de har forskjellige funksjoner for prosessering og informasjonslagring.<\/span><\/p>\n

Guos team, sammen med andre, som australske Cortical Labs, som trente hjerneceller til \u00e5 spille Pong i 2022<\/a>I en ny studie av bioinformatikk med levende nerveceller utforsker vi en mulig l\u00f8sning p\u00e5 disse utfordringene.\u00a0<\/span><\/p>\n

Disse hjerneorganoidene - selvorganiserte, tredimensjonale vevskulturer som ligner minihjerner - vokser frem fra stamceller under spesifikke vekstbetingelser.\u00a0<\/span><\/p>\n

De kan bli noen millimeter i diameter og inneholde opptil 100 millioner nerveceller. Til sammenligning har en menneskehjerne omtrent 100 milliarder nerveceller. Organoidene er plassert p\u00e5 toppen av en mikroelektrodeanordning, som b\u00e5de stimulerer organoidene og registrerer nerveaktiviteten. Guos team kaller dette oppsettet for \"Brainoware\".<\/span><\/p>\n

Brainoware er i bunn og grunn en ny form for kunstig intelligens som er ganske annerledes enn det vi vanligvis ser i datamaskiner og smarttelefoner. <\/span><\/p>\n

I stedet for \u00e5 bruke vanlige brikker, har forskerne laget en liten klynge av menneskelige hjerneceller<\/a> - hjerneorganoiden. Denne lille \"minihjernen\" er dyrket frem i et laboratorium fra stamceller, og den kan utf\u00f8re noen grunnleggende oppgaver som vi vanligvis forbinder med kunstig intelligens, som \u00e5 gjenkjenne talem\u00f8nstre.<\/span><\/p>\n

\"\"
A) Et diagram av \"Brainoware\"-systemet, som viser en hjerneorganoide (en labdyrket minihjerne) koblet til en enhet som registrerer og stimulerer dens elektriske aktivitet. B) Et mikroskopisk bilde av hjerneorganoidet, farget for \u00e5 fremheve de ulike celletypene, som modne nevroner, astrocytter, tidlige nevroner og progenitorceller, som viser den komplekse 3D-strukturen. Kilde: Naturelektronikk<\/a>.<\/figcaption><\/figure>\n

Slik fungerer det<\/span><\/h2>\n

\u00a0Hjerneorganoidet plasseres p\u00e5 en spesiell innretning som kan sende og lese av elektriske signaler. <\/span><\/p>\n

P\u00e5 denne m\u00e5ten kan forskerne kommunisere med organoiden, og p\u00e5 sett og vis l\u00e6re den \u00e5 reagere p\u00e5 bestemte m\u00f8nstre eller input. I studien trente de den til \u00e5 gjenkjenne ulike stemmer fra lydklipp.<\/span><\/p>\n

Et av de mest bemerkelsesverdige aspektene ved Brainware er at den l\u00e6rer og tilpasser seg. P\u00e5 samme m\u00e5te som en menneskehjerne blir bedre til oppgaver med \u00f8velse, forbedrer organoiden sin evne til \u00e5 gjenkjenne stemmer jo mer den blir eksponert for dem.\u00a0<\/span><\/p>\n

Dette bringer oss et skritt n\u00e6rmere \u00e5 skape kunstig intelligens som fungerer mer som den menneskelige hjernen, som er sv\u00e6rt effektiv og ikke trenger mye energi for \u00e5 fungere (omtrent som en liten lysp\u00e6re).<\/span><\/p>\n

Det finnes imidlertid utfordringer. Det er vanskelig \u00e5 dyrke disse hjerneorganoidene - de er vanskelige \u00e5 lage, vanskelige \u00e5 gjenskape konsekvent og varer ikke lenge, men teamet jobber med \u00e5 finne l\u00f8sninger.\u00a0<\/span><\/p>\n

Brainowares ytelse<\/span><\/h2>\n

I et uoverv\u00e5ket talegjenkjenningseksperiment ble organoidene trent opp til \u00e5 skille en enkelt stemme fra 240 lydopptak av \u00e5tte personer som ytret japanske vokallyder. Disse lydene ble konvertert til signalsekvenser og romlige m\u00f8nstre for organoidene.<\/span><\/p>\n

Til \u00e5 begynne med viste organoidene en n\u00f8yaktighetsgrad p\u00e5 omtrent 30 til 40%, som ble forbedret til 70 til 80% etter to dagers trening.\u00a0<\/span><\/p>\n

Mer om studien<\/span><\/h2>\n

Bioinspirert kunstig intelligens<\/span><\/a> tar noen forskjellige former, for eksempel <\/span>nevromorfe brikker<\/span><\/a> basert p\u00e5 biologiske nevroner. Dette g\u00e5r et skritt videre ved \u00e5 skape beregningsarkitektur fra biologiske organoider.\u00a0<\/span><\/p>\n

Her finner du mer informasjon om hvordan det fungerer:<\/span><\/p>\n

    \n
  1. Bioinspirert AI-maskinvare<\/b>: Studien, som er publisert i Nature Electronics, introduserer Brainoware, en ny AI-maskinvare som benytter biologiske nevrale nettverk i en hjerneorganoide. Dette markerer et fundamentalt skifte fra tradisjonelle hjerneinspirerte silisiumbrikker, og gir en mer autentisk emulering av hjernens funksjon.<\/span><\/li>\n
  2. Brainowares struktur og funksjonalitet<\/b>: Brainoware fungerer ved \u00e5 koble en hjerneorganoide, dyrket fra humane pluripotente stamceller, til en multielektrodeoppstilling med h\u00f8y tetthet. Dette oppsettet gj\u00f8r det mulig b\u00e5de \u00e5 overf\u00f8re elektriske signaler til organoidet og detektere nevrale responser. Organoidet har egenskaper som ikke-line\u00e6r dynamikk, hukommelse og evnen til \u00e5 behandle romlig informasjon.<\/span><\/li>\n
  3. Bruksomr\u00e5der som ble demonstrert i studien<\/b>: Teamet har brukt Brainoware i praktiske scenarier, som talegjenkjenning og prediksjon av ikke-line\u00e6re kaotiske ligninger (som H\u00e9non-kartet). Dette viser Brainowares evne til \u00e5 forbedre databehandlingsytelsen gjennom oppl\u00e6ring, noe som understreker potensialet for oppgaver som krever adaptiv l\u00e6ring.<\/span><\/li>\n
  4. Utfordringer og begrensninger<\/b>: Til tross for sin innovative tiln\u00e6rming st\u00e5r Brainoware overfor flere tekniske utfordringer, blant annet n\u00e5r det gjelder generering og vedlikehold av hjerneorganoider. I tillegg er maskinvaren avhengig av perifert utstyr, noe som hemmer potensialet. Med andre ord trenger du mye st\u00f8tteutstyr for at hjerneorganene skal fungere som de skal.\u00a0<\/span><\/li>\n
  5. Fremtidig retning og potensial<\/b>: Studien tyder p\u00e5 at Brainoware kan utvikle seg til et mer effektivt og sofistikert system dersom man gj\u00f8r fremskritt innen organoid-dyrking og l\u00f8ser praktiske problemer knyttet til organoider. Dette kan f\u00f8re til AI-maskinvare som i st\u00f8rre grad etterligner den menneskelige hjernens funksjon, noe som potensielt kan redusere energiforbruket.<\/span><\/li>\n<\/ol>\n

    I fremtiden kan denne typen biodatasystemer kanskje utf\u00f8re AI-oppgaver mer energieffektivt enn tradisjonelle silisiumbaserte brikker.\u00a0<\/span><\/p>\n

    Utviklingen innen bioinspirert AI fra i \u00e5r er sv\u00e6rt lovende n\u00e5r det gjelder \u00e5 hjelpe AI-industrien med \u00e5 overvinne begrensningene ved brute-force computing og skape energieffektive teknologier som er like elegante som naturen. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Klynger av menneskelige hjerneceller dyrket i petrisk\u00e5ler har blitt integrert med datamaskiner for \u00e5 oppn\u00e5 et grunnleggende niv\u00e5 av talegjenkjenning. Feng Guo, fra Indiana University Bloomington, forklarer om studien, som er publisert i Nature Electronics: \"Dette er en forel\u00f8pig demonstrasjon for \u00e5 vise at konseptet er gjennomf\u00f8rbart. Det er fortsatt en lang vei \u00e5 g\u00e5.\" Guo peker p\u00e5 to hovedutfordringer ved konvensjonell AI som denne formen for biologisk AI s\u00f8ker \u00e5 l\u00f8se: h\u00f8yt energiforbruk og de iboende begrensningene til silisiumbrikker, som deres distinkte prosesserings- og informasjonslagringsfunksjoner. Guos team, sammen med andre, som australske Cortical Labs,<\/p>","protected":false},"author":2,"featured_media":8195,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[350,203,101],"class_list":["post-8193","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-bio-inspired-ai","tag-biotech","tag-medtech"],"yoast_head":"\nResearchers perform AI speech recognition with human brain cells | DailyAI<\/title>\n<meta name=\"description\" content=\"Clusters of human brain cells cultivated in Petri dishes have been integrated with computers to achieve a fundamental level of speech recognition.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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