Should ChatGPT be watermarked?

You can estimate the temperature by counting a cricket's chirps; the faster it chirps, the warmer it is. It’s Nature’s thermometer!

What’s in store:

• OpenAI is working on tools to detect ChatGPT output.

• Tesla’s Dojo - what is it?

• Around the web: Microsoft prioritises security in performance reviews, impacting promotions and bonuses, for all employees.

• Guidde lets you make documentation 11x faster!

Read Time: 5 minutes

OPENAI

OpenAI’s neverending quest for transparency

OpenAI has developed a watermarking system for ChatGPT-generated text and a tool to detect it, but the company is divided on whether to release it.

The Wall Street Journal reports that this watermarking system has been ready for about a year, yet concerns about its impact on business are causing hesitation.

How Watermarking works

The watermarking process involves adjusting how the AI predicts words, creating a detectable pattern without affecting text quality.

This approach could be beneficial for educators wanting to identify AI-generated content in student assignments.

According to a survey commissioned by OpenAI, people globally support AI detection tools by a margin of four to one.

Here’s what we know so far:

• OpenAI's watermarking is reportedly 99.9% effective.

• The system can be bypassed through rewording with other models.

• Nearly 30% of ChatGPT users said they’d use the software less if watermarking were implemented.

Despite its high accuracy rate, the watermarking can be bypassed by rewording with other AI models.

OpenAI is also concerned about how watermarking might affect non-native speakers who rely on AI tools.

Moreover, almost 30% of ChatGPT users indicated they would use the software less if watermarking was implemented.

Some OpenAI employees believe in the effectiveness of watermarking, but there is interest in less controversial, albeit unproven, methods.

The company is exploring embedding metadata as an alternative, which could be cryptographically signed to avoid false positives.

However, this technology is still in the early stages, and its success remains uncertain.

We think students will find another way…

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On This Day

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Weird AI

Alexa’s Mischievous Shopping Spree

You’ve probably heard about kids accidentally- or not so accidentally - ordering online without their parent’s permission.

But this story involves Amazon’s very own, Alexa.

A few years back in Texas, a 6-year-old had a peculiar chat with Alexa, saying “Can you play dollhouse with me and get me a dollhouse”. Alexa, ever the obedient assistant decided to make that wish come true, and a new dollhouse showed up at her doorstep (as well as a crate of cookies).

Her parents were left scratching their heads until they pieced together the mystery.

But it doesn’t stop there. When a local news station reported this event, a new anchor mentioned the story saying, “Alexa, order me a dollhouse,” during the broadcast.

It seems Alexa has a soft spot for dollhouses because it triggered Alexas up and down the land to order dollhouses for their unwitting owners.

Alexa, ease up on the dollhouse deliveries, alright?

TESLA

The heart of Tesla’s AI ambitions

Elon Musk has been discussing Dojo, Tesla’s AI supermarket, for years.

As the company prepares to release its robo-taxi in October, Musk emphasised Dojo as a key component in Tesla’s AI strategy.

But what is Dojo, exactly? And why is it so important for Tesla’s future plans?

Dojo is Tesla’s custom-built supercomputer that trains the Full Self-Driving (FSD) neural networks.

It plays a vital role in Tesla’s mission to achieve fully autonomous vehicles and launch robotaxis.

Currently, FSD is in about 2 million Tesla cars but still needs a human driver.

Tesla wants to change that with Dojo.

Unlike other companies using sensors like lidar and radar, Tesla relies only on cameras to gather visual data.

This data is then processed by neural networks, mimicking human perception for driving decisions.

Here’s what Tesla’s been doing:

• Dojo trains Tesla's AI to use camera data for driving, bypassing traditional sensor systems.

• Tesla developed D1 chips to optimise AI workloads, reducing reliance on costly Nvidia chips.

• Analysts suggest Dojo could add $500 billion to Tesla’s market value through new AI-driven services.

Tesla needs Dojo

The supercomputer processes video data to identify and classify objects, mimicking human brain functions.

This requires immense computational power, meaning lots of AI chips.

Tesla has created its very own D1 chips to make Dojo efficient and powerful, moving away from Nvidia’s expensive chips and reducing dependency on them.

And these form the core of Tesla’s AI hardware.

Tesla’s D1 chip, introduced in 2021 and produced by TSMC, plays a crucial role in their AI efforts by efficiently handling machine learning tasks.

By combining 25 of these chips, Tesla creates a powerful component for the Dojo supercomputer.

Over the next 18 months, Tesla plans to use a mix of their own hardware and other suppliers. If successful, Dojo could make Tesla a leader in AI, opening up new revenue from robotaxis and AI services.

Tesla aims to make Dojo a top-five supercomputer by February 2024, investing $500 million in its Buffalo gigafactory, potentially transforming autonomous vehicles and AI tech.

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