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תוכן מסופק על ידי rickfu's collective on Huffduffer. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי rickfu's collective on Huffduffer או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
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Origin Story: Artificial Intelligence – Part One – Deus ex machina

 
שתפו
 

Manage episode 449896066 series 2507201
תוכן מסופק על ידי rickfu's collective on Huffduffer. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי rickfu's collective on Huffduffer או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
This week we begin the story of Artificial Intelligence. Since the launch of Chat-GPT in late 2022, we have been more excited, and anxious, about AI than ever before. It’s become a daily obsession. But the key question we are grappling with is the same as ever: can machines really ever develop human-style intelligence or merely imitate it? And what is human intelligence anyway? In part two we’ll be exploring the possible ramifications of AI, from the utopian to the dystopian and all points in between. But first, we explain how humanity’s long, ambivalent fascination with artificial life has brought us here. We start with premonitions of AI, from Mary Shelley’s Frankenstein to Isaac Asimov’s Three Laws of Robotics, and Ada Lovelace, the original AI sceptic, to Alan Turing and his famous test. Artificial Intelligence itself — the term and the field of study — began in 1956, at a summer school at Dartmouth University. While most computer scientists were working on ways for machines to partner with human intelligence — the personal computer, the internet — AI researchers dreamt of replacing it. For decades, AI development was a cycle of boom and bust. Extravagant claims attracted funding, talent and media attention, then their failure to materialise caused all three to collapse. AI became tarnished by its broken promises. But in the 21st century, the availability of vast troves of data and powerful new processors finally solved such stubborn challenges as image recognition and automatic translation, leading to the current AI gold rush. Along the way, we meet gamechanging scientists like Marvin Minsky and Geoffrey Hinton as well as landmark machines like ELIZA, the first chatbot, Shakey the robot and AlexNet, deep learning’s great leap forward. Why does the prospect of machine intelligence enthral and unnerve us? Why has AI proved so much more difficult than its pioneers imagined? How have fictional AIs like HAL and Skynet shaped the mythology of AI? And are Large Language Models like Chat-GPT just glorified autocomplete or a historic turning point in our relationship with machines? https://pod.link/1624704966/episode/c7ca68b5cf4f76defa69d14520ccc646
  continue reading

2017 פרקים

Artwork
iconשתפו
 
Manage episode 449896066 series 2507201
תוכן מסופק על ידי rickfu's collective on Huffduffer. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי rickfu's collective on Huffduffer או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
This week we begin the story of Artificial Intelligence. Since the launch of Chat-GPT in late 2022, we have been more excited, and anxious, about AI than ever before. It’s become a daily obsession. But the key question we are grappling with is the same as ever: can machines really ever develop human-style intelligence or merely imitate it? And what is human intelligence anyway? In part two we’ll be exploring the possible ramifications of AI, from the utopian to the dystopian and all points in between. But first, we explain how humanity’s long, ambivalent fascination with artificial life has brought us here. We start with premonitions of AI, from Mary Shelley’s Frankenstein to Isaac Asimov’s Three Laws of Robotics, and Ada Lovelace, the original AI sceptic, to Alan Turing and his famous test. Artificial Intelligence itself — the term and the field of study — began in 1956, at a summer school at Dartmouth University. While most computer scientists were working on ways for machines to partner with human intelligence — the personal computer, the internet — AI researchers dreamt of replacing it. For decades, AI development was a cycle of boom and bust. Extravagant claims attracted funding, talent and media attention, then their failure to materialise caused all three to collapse. AI became tarnished by its broken promises. But in the 21st century, the availability of vast troves of data and powerful new processors finally solved such stubborn challenges as image recognition and automatic translation, leading to the current AI gold rush. Along the way, we meet gamechanging scientists like Marvin Minsky and Geoffrey Hinton as well as landmark machines like ELIZA, the first chatbot, Shakey the robot and AlexNet, deep learning’s great leap forward. Why does the prospect of machine intelligence enthral and unnerve us? Why has AI proved so much more difficult than its pioneers imagined? How have fictional AIs like HAL and Skynet shaped the mythology of AI? And are Large Language Models like Chat-GPT just glorified autocomplete or a historic turning point in our relationship with machines? https://pod.link/1624704966/episode/c7ca68b5cf4f76defa69d14520ccc646
  continue reading

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