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A direct appeal to Sundar Pichai, CEO of Alphabet, to please fix Google Finance’s most basic feature

Alphabet is a remarkable entity. Today, millions of people will fire up Google Chrome, check their Gmail, and then flick over to YouTube — now the biggest thing in TV, and potentially worth some $550 billion — all while Alphabet’s self-driving car division, Waymo, safely delivers thousands of people to their desired destination... and Google itself handles over 150,000 search queries every single second.

But one tiny bug in the Finance product is enough to make me forget all of that.

Disclaimer: If you aren’t in the mood to dive into a very petty — largely unimportant — gripe about stock charts, please stop reading.

When searching the web for a stock and using Google Finance’s “year to date” return function on its interactive module, the calculation is always, bafflingly, wrong. Take Tesla’s stock as an example.

Tesla stock
Sherwood News

Per this Google module, Tesla’s stock is down 31.67% this year. From memory that sounds broadly correct — Tesla is having a bad year after all — but it’s not quite right.

Let’s do the calculation manually. Using the interactive chart, we can calculate the change from the end of December 31 to yesterday’s close (March 31).

Tesla YTD 2 Google Finance
Screenshot from Google

Doing that, we get -35.83%. About a 4% difference.

So, what’s going on?

It turns out that Google Finance is using the close price from January 2 in the first case, essentially ignoring the first day of trading. We can see this in the below screenshot: drawing a line from January 2 to March 31 gives us Google’s YTD change of 31.67%. But, of course, January 2 should be counted. In this case, Tesla moved quite a bit on the day!

Tesla YTD 3 Google Finance
Screenshot from Google

Rival provider Yahoo Finance correctly tells us it’s -35.83% on its website.

Yahoo Finance
Screenshot from Yahoo Finance

The weirdest thing, however, is that if I navigate to the actual Google Finance website (rather than just using the interactive module that appears at the top of Google Search), the problem fixes itself.

Still, Sundar, if you’re reading this, can you help us out here?

When searching the web for a stock and using Google Finance’s “year to date” return function on its interactive module, the calculation is always, bafflingly, wrong. Take Tesla’s stock as an example.

Tesla stock
Sherwood News

Per this Google module, Tesla’s stock is down 31.67% this year. From memory that sounds broadly correct — Tesla is having a bad year after all — but it’s not quite right.

Let’s do the calculation manually. Using the interactive chart, we can calculate the change from the end of December 31 to yesterday’s close (March 31).

Tesla YTD 2 Google Finance
Screenshot from Google

Doing that, we get -35.83%. About a 4% difference.

So, what’s going on?

It turns out that Google Finance is using the close price from January 2 in the first case, essentially ignoring the first day of trading. We can see this in the below screenshot: drawing a line from January 2 to March 31 gives us Google’s YTD change of 31.67%. But, of course, January 2 should be counted. In this case, Tesla moved quite a bit on the day!

Tesla YTD 3 Google Finance
Screenshot from Google

Rival provider Yahoo Finance correctly tells us it’s -35.83% on its website.

Yahoo Finance
Screenshot from Yahoo Finance

The weirdest thing, however, is that if I navigate to the actual Google Finance website (rather than just using the interactive module that appears at the top of Google Search), the problem fixes itself.

Still, Sundar, if you’re reading this, can you help us out here?

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FT: Meta considering “tens of billions” in new capital to fund AI

Just days after Google announced a monster $85 billion upsized equity raise, the extremely profitable Meta is seeking to sell “tens of billions of dollars” in stock, according to a new report from the Financial Times.

Meta is planning on spending between $125 billion and $145 billion on AI capital expenditure this year alone.

Shares dropped more than 5% on the news.

tech

FT: Anthropic staff helping the NSA use Mythos for offensive cyberattacks

Anthropic’s Mythos AI model was deemed too dangerous to release to the public, with the company citing its ability to orchestrate novel cyberattacks.

And that’s just what the National Security Agency is doing, with the help of Anthropic staff embedded at the agency, according to a report from the Financial Times.

Only a small number of companies and US allies have been given access to the advanced model, which means America’s adversaries have not had the chance to shore up their defenses against the AI model’s new offensive capabilities.

The arrangement is especially unusual as the Pentagon has deemed Anthropic’s AI a national security supply chain risk — effectively blacklisting it for defense work — in response to the company’s refusal to allow its technology to be used for any legal application, which could include autonomous killing or mass surveillance. Anthropic is currently suing the US government to fight the determination.

Only a small number of companies and US allies have been given access to the advanced model, which means America’s adversaries have not had the chance to shore up their defenses against the AI model’s new offensive capabilities.

The arrangement is especially unusual as the Pentagon has deemed Anthropic’s AI a national security supply chain risk — effectively blacklisting it for defense work — in response to the company’s refusal to allow its technology to be used for any legal application, which could include autonomous killing or mass surveillance. Anthropic is currently suing the US government to fight the determination.

tech

Longtime Tesla bear JPMorgan upgraded Tesla and raised its price target to $475 from $145

For more than a decade, JPMorgan was Wall Streets most stubborn Tesla skeptic, anchored by auto analyst Ryan Brinkman’s strict focus on traditional car fundamentals and near-term delivery numbers.

But JPM recently handed coverage of the stock to a new analyst, Rajat Gupta, who is throwing that playbook out the window. In a note Friday, the firm upgraded Tesla to neutral from underweight and raised its price target 228% to $475 from $145. (The analyst consensus on FactSet is $403.) Instead of focusing on the company’s struggling vehicle business, the new analyst is orienting himself more toward Tesla’s idea of the future, now modeling Tesla’s physical AI and robotaxi fleets all the way out to the year 2040.

Here are the main reasons for the capitulation:

  • Looking past the car lot: Gupta argues that Tesla is at the forefront of physical AI, entering uncharted TAMs” and therefore deserves the benefit of the doubt to be valued on LT earnings potential rather than near-term speed bumps.

  • Unmatched vertical integration: Teslas control over everything from battery cells to custom silicon gives it a massive moat. JPM notes this starting point advantage is unmatched at an industrial level scale” and “still somewhat under-appreciated and misunderstood.

  • The AWS flywheel effect: Deploying Optimus robots inside its own factories should not only lower COGS for the base automotive business, but more importantly, help validate the product at an industrial scale.” Gupta called it “a classic flywheel effect, somewhat analogous to AWS and Kiva at AMZN.

For Tesla bulls who have argued for years that this is an AI company and not a carmaker, JPM’s sudden $3.9 trillion valuation model is the ultimate validation.

skynet terminator

Anthropic ponders self-improving AI

Anthropic says Claude already writes 80% of its code. A new post asks what happens when the models can improve themselves — and whether anyone could stop them.

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