Computerspeak by Alexandru Voica

Computerspeak by Alexandru Voica

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Computerspeak by Alexandru Voica
Computerspeak by Alexandru Voica
Why machine translation still struggles with the world's most popular languages; what's next for generative video; Adobe bets on ethical AI; inside Stability AI's implosion
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Why machine translation still struggles with the world's most popular languages; what's next for generative video; Adobe bets on ethical AI; inside Stability AI's implosion

Chatbot hype hits reality; the fight for AI talent; Databricks' DBRX is the most powerful open source LLM; Ray Ban smart glasses get an AI upgrade; Sakana AI introduces evolutionary AI algorithm;

Alexandru Voica's avatar
Alexandru Voica
Mar 29, 2024
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Computerspeak by Alexandru Voica
Computerspeak by Alexandru Voica
Why machine translation still struggles with the world's most popular languages; what's next for generative video; Adobe bets on ethical AI; inside Stability AI's implosion
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In an article for The Atlantic this week, Louise Matsakis (check out her recently launched newsletter You May Also Like!) discusses how advances in generative AI are leading to the proliferation of automatic translation tools that could make learning new languages seem less necessary and therefore cause a decline in enrollment for foreign language courses in the United States and other countries.

Louise describes how she used an AI app to create a deepfake video of herself speaking fluent Chinese, despite only having basic skills in the language, and interviews experts who argue that something profound may be lost when we rely solely on machine translation: the ability to truly understand other cultures and ways of thinking that comes from learning a new language.

While AI excels at technical translation, it has historically lacked the cultural context and nuance that humans provide. Traditional machine translation tools have struggled with metaphors, cultural references, and choosing the most accurate phrasing. But newer AI models based on transformer architectures are improving machine translation by going beyond simple word swaps. They learn the intricate dance of language – syntax, context, and cultural references – resulting in translations that are more natural and accurate. This paves the way for real-time conversation translation tools that can bridge the gap between languages instantaneously.

The benefits are undeniable: global collaboration can flourish, fostering innovation and cultural exchange. Imagine attending a virtual conference where every participant can understand presentations regardless of their native tongue. Language-based discrimination could become a thing of the past, as job markets open up and cultural understanding deepens.

However, a world without language barriers is not without its complexities. There's a beauty in the poetry and humor specific to each language. Will constant translation homogenize these linguistic treasures? Furthermore, cultural identity is often interwoven with language. Will the ability to seamlessly switch languages dilute this connection?

But perhaps the most interesting hurdle for machine translation lies in low-resource languages – those with limited written materials and digital presence. Historically, the term low-resource languages was used to describe relatively obscure tongues spoken by small populations. With too little example data to learn from, large language models systems struggle with word ordering, idioms, context, and nuanced meaning so the resulting translations for low resource languages are often wrong or simply incomprehensible. For example, in October 2023, Instagram started adding the word “terrorist” to the biographies of some of its users because it incorrectly translated a word from Arabic.

@ytkingkhanMeta definitely needs to address this (though I couldnt find an official TikTok account for them) #palestine #arab #desi #muslim
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For years, there has been an assumption in the field of machine translation that some of the world's most widely spoken languages like French, Spanish, Russian and Arabic have ample data for AI systems to learn from. However, AI researchers I’ve spoken to have shared a worrying trend: even languages considered mainstream and high-resource are at risk of becoming low-resource.

Major demographic, cultural, and technological shifts are putting some of the world's linguistic giants in jeopardy. The rise of regional dialects and slangs, accelerated by social media and digital subcultures, has fractured languages like Arabic into numerous divergent varieties. While a mother tongue may have abundant learning data overall, its vernacular offshoots are becoming low-resource languages unto themselves.

Furthermore, script styles and new character sets are evolving faster than ever. Regional writing systems for the Arabic script proliferate new glyphs and ligatures adapted for speed and new vocabularies. These don't match established encodings, creating low-resource problems within high-resource languages.

Most concerning is the decline of linguistic diversity worldwide as globalizing forces lead to language extinction at unprecedented rates. Therefore, as native speakers dwindle, these major world languages are now at risk. For example, in cities such as Riyadh, Dubai or Abu Dhabi, English has become the go-to language for young people, creating a situation where many people from the Middle East struggle to write or even speak in Arabic.

The low-resource crisis extends beyond machine translation. As languages lose speakers and stop evolving new vocabulary and usage examples, training data for all language AI like chatbots, video captioning, and text summarization will grow stale and inadequate. Already, we've seen preliminary effects with technical jargon and academic domains where English training data is relatively low-resource compared to general-use English corpora. Enterprise language models struggle with esoteric fields from medicine to finance despite English's high-resource reputation.

Solutions are urgently required to preserve linguistic resources and dynamically adapt machine learning to evolving low-resource languages and dialects. Otherwise, the machine translation systems we take for granted today will become increasingly error-prone and useless across more areas of modern communication.

Despite these complexities, the potential of AI-powered real-time translation is undeniable. The road ahead involves creating technology that preserves the richness of languages while fostering global understanding.

And now, here are this week’s news:

❤️Computer loves

Our top news picks for the week - your essential reading from the world of AI

  • MIT Technology Review: What’s next for generative video

  • Fortune: In 40 years as a founder-CEO, Michael Dell turned his dorm-room PC company into a tech giant. Can he cash in on the AI boom?

  • MIT Technology Review: How Adobe’s bet on non-exploitative AI is paying off

  • The Atlantic: The End of Foreign-Language Education

  • Bloomberg: AI Is Putting the Silicon Back in Silicon Valley

  • WSJ: Want to Know if AI Will Take Your Job? I Tried Using It to Replace Myself

  • The Information: This New Orleans museum uses AI to allow visitors to speak with WWII veterans

  • Fortune: Inside the $1 billion love affair between Stability AI’s ‘complicated’ founder and tech investors Coatue and Lightspeed—and how it turned bitter within months

  • Washington Post: AI hustlers stole women’s faces to put in ads. The law can’t help them.

  • New York Times: Meta’s Smart Glasses Are Becoming Artificially Intelligent. We Took Them for a Spin.

  • FT: How Silicon Valley’s ‘Oppenheimer’ found lucrative trade in AI weapons

  • New Yorker: The Lifelike Illusions of A.I.

  • WSJ: The Fight for AI Talent: Pay Million-Dollar Packages and Buy Whole Teams

  • VentureBeat: Sakana AI’s evolutionary algorithm discovers new architectures for generative models

  • MIT Technology Review: The tech industry can’t agree on what open-source AI means. That’s a problem.

  • Axios: Chatbot letdown: Hype hits rocky reality

  • Wired: Inside the Creation of the World’s Most Powerful Open Source AI Model

⚙️Computer does

AI in the wild: how artificial intelligence is used across industry, from the internet, social media, and retail to transportation, healthcare, banking, and more

  • MIT Technology Review: How three filmmakers created Sora’s latest stunning videos

  • Time: Can AI Help You Do Your Taxes?

  • MIT Technology Review: AI could make better beer. Here’s how.

  • Business Insider: AI is helping fragrance companies unlock the sensational possibilities of smell

  • 9to5Google: Gemini updated to automatically start Google Maps navigation

  • FT: Media groups look to AI tools to cut costs and complement storytelling

  • Fortune: Retailers like Matalan are turning to AI to tell you how your next top is going to look—and to convince you to buy it

  • The Verge: Airtable brings AI summarization to paying users

  • BBC: Could AI take the grind out of accountancy?

  • The Economist: Artificial intelligence is taking over drug development

  • FT: AI is accelerating the energy transition, say industry leaders

  • Business Insider: A Microsoft-powered medical AI spotted cancer in 11 women where doctors didn't

  • Bloomberg: Visa Adds New AI Tools to Help Fight Digital Fraud on Payments

  • TechCrunch: Vibrant Planet uses AI for land mapping and improving climate resiliency

  • The Verge: Google adds ratings to go with its new AI tools for shoppers

  • The Guardian: AI to track hedgehog populations in pioneering UK project

  • Reuters: Romanian state agency turns to AI to help farmers tap EU funds

  • VentureBeat: OpenAI shows off first examples of third-party creators using Sora

🧑‍🎓Computer learns

Interesting trends and developments from various AI fields, companies and people

  • VentureBeat: AI21 Labs juices up gen AI transformers with Jamba

  • The Verge: How a Windows shake-up could position Microsoft to capitalize on AI PCs

  • VentureBeat: Google DeepMind unveils 'superhuman' AI system that excels in fact-checking, saving costs and improving accuracy

  • Reuters: Musk's Grok-1.5 AI chatbot to be available next week

  • Fortune: Why Amazon’s multi-billion dollar AI alliance with Anthropic isn’t the game-changer it needs to remain king of the cloud

  • Fast Company: Researchers tap AI and patternless collections to help predict catastrophic failure

  • VentureBeat: SambaNova announces new AI Samba-CoE v0.2 that already beats Databricks DBRX

  • Business Insider: Inside Big Tech's nasty battle for coveted AI talent

  • Axios: Oracle gives NetSuite an AI upgrade

  • VentureBeat: Microsoft launches new Azure AI tools to cut out LLM safety and reliability risks

  • VentureBeat: Lightning AI launches next-gen AI compiler ‘Thunder’ to accelerate model training

  • Fortune: As OpenAI targets Hollywood with Sora, Runway’s CEO is waiting for the $86 billion Goliath with a ‘sling and a stone’

  • Reuters: French company Valeo to use more Google Cloud AI tools

  • Business Insider: Some of Silicon Valley's biggest names are wading into the battle for AI expertise

  • Bloomberg: Amazon Bets $150 Billion on Data Centers Required for AI Boom

  • Business Insider: Microsoft customers complain Copilot doesn't work as well as ChatGPT. Microsoft says they're not using it right.

  • Business Insider: Mark Zuckerberg says Nvidia CEO Jensen Huang is basically the Taylor Swift of tech

  • Business Insider: AI is making gadgets weird again — and it could radically redesign your smartphone

  • Business Insider: Palmer Luckey says Anduril is working on AI weapons that 'give us the ability to swiftly win any war'

  • Business Insider: Using AI in classrooms could help or hurt students — that's why educators should teach tech literacy, scholars say

  • The Telegraph: BBC defends replacing actress with AI for voiceover

  • MIT Technology Review: Four things you need to know about China’s AI talent pool 

  • WSJ: Companies Are Seeking Real-World Supply-Chain Gains in New AI Tools

  • Reuters: New AI benchmark tests speed of responses to user queries

  • Fortune: Businesses are in the ‘third quarter’ of the AI contest, says Walmart International’s CEO—but people are still figuring out how best to use the new tech

  • Bloomberg: Salesforce Paid $20 Million for the Face of Its AI Strategy

  • TechCrunch: Adobe’s Firefly Services makes over 20 new generative and creative APIs available to developers

  • Wired: Is AI the Future of NPCs?

  • VentureBeat: Nvidia triples and Intel doubles generative AI inference performance on new MLPerf benchmark

  • The Verge: OpenAI is experimenting with sharing revenue with builders in its GPT Store

  • TechCrunch: Adobe’s GenStudio brings brand-safe generative AI to marketers

  • CNBC: CEO of Chinese AI company 4Paradigm discusses business outlook under U.S. sanctions

  • Reuters: Musk's xAI to enable chatbot Grok for all premium subscribers of X

  • FT: Financial services counting on AI for a productivity boost

  • Business Insider: Big tech's desperate scramble for AI talent

  • Fortune: Marc Benioff alludes to the market’s possible AI oversaturation by joking about a “genius” toothbrush

  • FT: Academics express confidence that they and AI can work together

  • Business Insider: Stability AI founder's jokes about Satya Nadella's influence have a dark truth to them

  • Business Insider: Sergey Brin personally called a Google employee to convince them to turn down a job at OpenAI: report

  • FT: Healthcare professionals demonstrate immunity to AI

  • Business Insider: Watch the crazy AI short films and videos created by artists with early access to OpenAI's Sora tool

  • Business Insider: Why some creators are limiting or stopping their use of AI tools

  • The Economist: The AI doctor will see you…eventually

  • The Economist: Medical AIs with human faces are their way

  • The Economist: Can artificial intelligence make health care more efficient?

  • MIT Technology Review: Apple researchers explore dropping “Siri” phrase & listening with AI instead

  • WSJ: CFOs Tackle Thorny Calculus on Gen AI: What’s the Return on Investment?

  • Business Insider: Managers are worrying that their salaries will get cut because of AI, a survey found

  • Axios: The future of AI: Personalized systems tuned to your needs, Amazon exec says

  • The Verge: Financial Times tests an AI chatbot trained on decades of its own articles

  • TechCrunch: Large language models can help home robots recover from errors without human help

  • The A.I. Boom Makes Millions for an Unlikely Industry Player: Anguilla

  • The Information: A Booming Nvidia Supplier Says AI Costs Need to Drop

  • Business Insider: Sam Altman may have Siri and Alexa in his sights after OpenAI filed a 'digital voice assistant' trademark application

  • TechCrunch: Can you hear me now? AI-coustics to fight noisy audio with generative AI

  • Reuters: Behind the plot to break Nvidia’s grip on AI by targeting software

  • Reuters: Can artificial intelligence extend healthcare to all?

  • Reuters: Tokyo, Tokyo, make me a match! Metropolis hopes AI app will spur marriages

  • The Verge: What our shopping haul taught us about the promise of AI

  • The Information: Meta Pursues AI Talent With Quick Offers, Emails From Zuckerberg

  • Wired: Large Language Models’ Emergent Abilities Are a Mirage

  • Fast Company: One year in, Khan Academy’s AI has 65,000 students, and is still learning new skills

  • The Verge: AI-generated blues misses a human touch — and a metronome

  • VentureBeat: Pure Storage, Nvidia partner to democratize AI with new infrastructure solutions

  • Bloomberg: The Economist Who Believes AI Will Be Great for the Middle Class

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