⚡️@business: Alphabet fell by the most in more than three months on concerns that its new artificial intelligence chatbot Bard may yield inaccurate responses
Just watched the 'Google Live from Paris' event and it looked like a non-event to me. It seems that the livestream event was set private after it ended. (It was unlisted to begin with) They even forgot the phone used to demonstrate multisearch. This suggests to me that Google is finally getting disrupted and are scrambling of desperation because of the release of ChatGPT.
@sundarpichai: 1/ In 2021, we shared next-gen language + conversation capabilities powered by our Language Model for Dialogue Applications (LaMDA). Coming soon: Bard, a new experimental conversational #GoogleAI service powered by LaMDA.
@sundarpichai: 2/ Bard seeks to combine the breadth of the world's knowledge with the power, intelligence, and creativity of our large language models. It draws on information from the web to provide fresh, high-quality responses. Today we're opening Bard up to trusted external testers.
3/ We'll combine their feedback with our own internal testing to make sure Bard's responses meet our high bar for quality, safety, and groundedness and we will make it more widely available in coming weeks. It's early, we will launch, iterate and make it better.
4/ As people turn to Google for deeper insights and understanding, AI can help us get to the heart of what they're looking for. We're starting with AI-powered features in Search that distill complex info into easy-to-digest formats so you can see the big picture then explore more
5/ Developers can soon try our Generative Language API, initially powered by LaMDA with a range of models to follow. Over time, our goal is to create a set of tools and APIs that will make it easy for others to build more innovative applications with AI.
#45 Feb 3, 2023
⚡️@AlphaSignalAI: JUST IN. Google invests $300 million in Anthropic as race to compete with ChatGPT heats up Anthropic was founded in 2021 by the team behind AI breakthroughs such as GPT-3 and Reinforcement Learning from Human Feedback (RLHF).
⚡️nasdaq.com: The Top Companies in the Cloud Computing Space
[Transcription] Google (GOOG, GOOGL) ranks among the top cloud players with a worldwide market share of 11%.
Over the past few years, Google has intensified its efforts to catch up with the leaders in cloud computing. During FY2017 (January–December), the revenue from Google Cloud was $4.05 billion, equivalent to 3.7% of its overall revenue, which touched double-digit figures at $13.06 billion in FY2020.
In FY2021, its revenue from cloud was registered at $19.2 billion, an increase of 47%. During the first three quarters of FY2022, Google’s cloud revenue touched $18.96 billion.
Alphabet is expected to report earnings for FY2022 on February 2, 2023.
The tech giant unexpectedly announced a 6% reduction in its workforce. Why did this happen, which areas are impacted, and why is Apple unlikely to follow suit?
⚡️@cspan (1): U.S. Attorney General Merrick Garland announces lawsuit again Google: "We alleged that Google has used anti-competitive exclusionary and unlawful conduct to eliminate or severely diminish any threat to its dominance over digital advertising technologies."
⚡️nowthisnews (2): Attorney General Merrick Garland on Tuesday: 'For 15 years, Google has pursued a course of anticompetitive conduct that has allowed it to halt the rise of rival technologies'
⚡️stream.alpha-sense.com: Former AI Product Manager Does Not Think ChatGPT Is a Big Threat to GOOGL's Core Search Business
[Transcription] EC-010423-126555
Call Summary
1. Believes GOOGL has similar LLMs in-house and will implement them over time, but what Chat GPT doesn't have is GOOGL's massive distribution globally, which will be difficult for anyone to penetrate.
2. Thinks that by 2030, ~90% of content on the internet will be produced by generative AI vs ~1% in 2021.
3. In the expert's opinion, compute capacity will benefit from the increase in AI workloads, but growth will be partially offset by models becoming smaller and more efficient and semis will continue to become more powerful and efficient.
Table of contents
Comparison between ChatGPT and Google
ChatGPT as a possible threat to Google
Concept of a hyper-personalized search system
Microsoft as an investor for OpenAl
Distribution advantage of Google over ChatGPT
Possible disruption within Google
Compute costs within Al and ChatGPT
Other interesting developments within the search engine spa
Spend on the development capacity for new Al applications
Tweet #1 The future could well be one of generative content created by generative AI. Generative AI is exploding, predictions from ~1% in 2021 to ~90% in 2030. From images, videos, text, code, music and so much more. Coding is important, but could well be less so going forward.
Tweet #2 Believes Google has similar Large-Language Model (LLMs) in-house (matches / potentially better) and will implement them over time. But what Chat GPT doesn't have is its’ massive distribution globally, which will be difficult for anyone to penetrate.
Tweet #3 Moving to hyper personalized synthesized responses that figure out the best stuff from multiple web pages. The wrong question to ask is if ChatGPT is a threat to Google. The right question to ask is what is the new paradigm of search and what is Google going to do about it?
Tweet #4 Challenge with Factuality, Confidence, etc. They have a way of writing or synthesizing something with extremely high confidence. They will give something which could be absolutely wrong, but say it so well with absolute certainty. That’s the real challenge.
Tweet #5 Possible opportunity for Microsoft to learn, provide a new user experience and maybe win some market share from Google (as they could be slow). Of opinion that Google is taking backseat, allowing Microsoft to de-risk first, then ensure quality before releasing anything.
Tweet #6 Less worried about Google not having the technology or means to get there, but more concerned about Google’s risk-taking ability and appetite for failure and GTM. Reckons Google will showcase the technology even if they don’t launch it.
Tweet #7 Large and expensive now, the models should get smaller (improved optimizations), cheaper (with lower compute cost) and more efficient over time. Right now, estimates cost of one ChatGPT query is probably 100-200X more than one Google Search Query.
Tweet #8 Generative AI is still in the exponential curve of technological progress, its impact is going to rapid and only increase, and will be challenging.
#32 Jan 20, 2023 🔴 rumors
🧷 Google Calls In Help From Larry Page and Sergey Brin for A.I. Fight
The New York Times
#31 Jan 20, 2023
⚡️Synthedia: The Most Interesting Analysis of the Generative AI Market to Date Has Arrived
⚡️SquawkCNBC: $GOOGL is the latest mega-cap tech firm to announce a fresh round of layoffs. @stevekovach breaks down what's happening in the #BigTech job market:
⚡️blog.google: A difficult decision to set us up for the future
Screenshot (*color profile edited. Source blog.google, Alphabet, Inc.
[Transcription] Sundar sent the following email to Google employees earlier today.
Googlers,
I have some difficult news to share. We’ve decided to reduce our workforce by approximately 12,000 roles. We’ve already sent a separate email to employees in the US who are affected. In other countries, this process will take longer due to local laws and practices.
This will mean saying goodbye to some incredibly talented people we worked hard to hire and have loved working with. I’m deeply sorry for that. The fact that these changes will impact the lives of Googlers weighs heavily on me, and I take full responsibility for the decisions that led us here.
Over the past two years we’ve seen periods of dramatic growth. To match and fuel that growth, we hired for a different economic reality than the one we face today.
I am confident about the huge opportunity in front of us thanks to the strength of our mission, the value of our products and services, and our early investments in AI. To fully capture it, we’ll need to make tough choices. So, we’ve undertaken a rigorous review across product areas and functions to ensure that our people and roles are aligned with our highest priorities as a company. The roles we’re eliminating reflect the outcome of that review. They cut across Alphabet, product areas, functions, levels and regions.
To the Googlers who are leaving us: Thank you for working so hard to help people and businesses everywhere. Your contributions have been invaluable and we are grateful for them.
While this transition won’t be easy, we’re going to support employees as they look for their next opportunity.
In the US:
We’ll pay employees during the full notification period (minimum 60 days).
We’ll also offer a severance package starting at 16 weeks salary plus two weeks for every additional year at Google, and accelerate at least 16 weeks of GSU vesting.
We’ll pay 2022 bonuses and remaining vacation time.
We’ll be offering 6 months of healthcare, job placement services, and immigration support for those affected.
Outside the US, we’ll support employees in line with local practices.
As an almost 25-year-old company, we’re bound to go through difficult economic cycles. These are important moments to sharpen our focus, reengineer our cost base, and direct our talent and capital to our highest priorities.
Being constrained in some areas allows us to bet big on others. Pivoting the company to be AI-first years ago led to groundbreaking advances across our businesses and the whole industry.
Thanks to those early investments, Google’s products are better than ever. And we’re getting ready to share some entirely new experiences for users, developers and businesses, too. We have a substantial opportunity in front of us with AI across our products and are prepared to approach it boldly and responsibly.
All this work is a continuation of the “healthy disregard for the impossible” that’s been core to our culture from the beginning. When I look around Google today, I see that same spirit and energy driving our efforts. That’s why I remain optimistic about our ability to deliver on our mission, even on our toughest days. Today is certainly one of them.
I’m sure you have many questions about how we’ll move forward. We’ll be organizing a town hall on Monday. Check your calendar for details. Until then, please take good care of yourselves as you absorb this difficult news. As part of that, if you are just starting your work day, please feel free to work from home today.
-Sundar
#28 Jan 19, 2023
⚡️@unusual_whales: Google, $GOOGL,is deferring a portion of employees’ year-end bonus checks, according to documents viewed by CNBC, as the company moves toward permanently pushing back payouts.
[Transcription] As Google has swelled in size to over 186,000 workers, many of its employees and even its CEO have complained that the company has become too slow, too bureaucratic, and not productive enough. [...]
"Google is a place that prides itself on moving quickly to tackle world-scale problems," Alex Komoroske, a former Google program manager who worked across products including Chrome and Maps, wrote. "But more recently it's started to feel way, way slower. Accomplishing even seemingly simple things seems to take forever."
The presentation titled "Why everything is so darn hard at Google," posited that Google's size and bottom-up organizational structure have caused it to slow dramatically in recent years. Komoroske believes the root of the problem is all about what he calls the "hidden force." [...]
"Google is basically a slime mold," Komoroske wrote, placing Google on a sliding scale from top-down to bottom-up structures. Komoroske said Google stands out by being further toward the bottom-up end of the scale. [...]
Komoroske said that a slime mold "can do amazing things" by creating more value than the sum of its parts. At the same time, the larger this type of organization grows, the more processes can slow down because many parts act independently, leading to "messy" behavior that can be "hard to predict" and control. [...]
Komoroske suggested there's no easy solution to the problem, but wrote that it's something companies shouldn't ignore.
A generic version of the presentation can be found on Komoroske’s blog. It’s a lot of slides, but he explains things very clearly.
I recommend it to better understand why scaling is such a challenge, and why lots of little frictions can have such a huge impact on output
Editor's Note: Today we published a piece outlining our perspective on the beneficial and transformational potential of AI, and our focus on being bold and responsible in both developing it and bringing it to users and society.
[Transcription] We believe that AI is a foundational and transformational technology that will provide compelling and helpful benefits to people and society through its capacity to assist, complement, empower, and inspire people in almost every field of human endeavor. It has the potential to contribute to tackling some of society’s most pressing challenges and opportunities, from the everyday to the more creative and imaginative.
As an information and computer science company, we aim to and have been at the forefront of advancing the frontier of AI through our path-breaking and field-defining research to develop more capable and useful AI. From this research and development, we are bringing breakthrough innovations into the real world to assist people and benefit society everywhere through our infrastructure, tools, products, and services, as well as through enabling and working with others to benefit society. We are also pursuing innovations that will help to unlock scientific discoveries and to tackle humanity’s greatest challenges and opportunities. Many of our innovations are already assisting and benefiting people (in some cases billions of people), communities, businesses, and organizations, and society broadly—with more such innovations still to come.
At the same time, we understand that AI, as a still-emerging technology, poses various and evolving complexities and risks. Our development and use of AI must address these risks. That’s why we as a company consider it an imperative to pursue AI responsibly. We are committed to leading and setting the standard in developing and shipping useful and beneficial applications, applying ethical principles grounded in human values, and evolving our approaches as we learn from research, experience, users, and the wider community.
We also believe that getting AI right—which to us involves innovating and delivering widely accessible benefits to people and society, while mitigating its risks— must be a collective effort involving us and others, including researchers, developers, users (individuals, businesses, and other organizations), governments, regulators, and citizens. It is critical that we collectively earn public trust if AI is to deliver on its potential for people and society. As a company, we embrace the opportunity to work with others to get AI right.
We are convinced that the AI-enabled innovations we are focused on developing and delivering boldly and responsibly are useful, compelling, and have the potential to assist and improve lives of people everywhere—this is what compels us. And we are excited about what lies ahead in 2023 and beyond as we get ready to share some new innovative experiences!
– James Manyika, Jeff Dean, Demis Hassabis, Marian Croak and Sundar Pichai
Our perspective, focus and principled approach in 5 parts
The following outlines how we think about and approach AI in five key parts. Each part will evolve as our innovations progress and as we learn more from research, experience, users, and the wider community.
Why we’re developing AI
To what end?
Our understanding of the complexities and risks
Our approach to Responsible AI
Why a collective approach to Responsible AI is needed
⚡️@googlecloud: #GoogleCloudPrediction: By 2025, 90% of data will be actionable in real-time using #ML. Imagine the incredible innovation this will unlock ↓
[Transription] Despite the murmurs, Google is still leading the AI race with its Pathways Language Model (PaLM), released earlier this year.
PaLM can be scaled up to 540 billion parameters, which means that the performance across tasks keeps increasing with the model’s increasing scale, thereby unlocking new capabilities. In comparison, GPT-3 only has about 175 billion parameters.
Google’s language model is trained with the Pathways system, which allows it to generalise tasks across a variety of domains and tasks while also being highly efficient.
Vaclav Kosar's Software & Machine Learning Blog: PaLM Training Dataset. Source: Google Search
#15 Dec 29, 2022
⚡️GoogleQuantumAI: With one click, you can learn how to begin building your custom QVM and use it to make circuits that perform well on current quantum hardware.
⚡️@TheShortBear: The thought that CHATGPT could fully disrupt $GOOGL is pretty interesting. Most will not have read into either what you need in order to create an AI or what $GOOGL has been doing for the last years. If anything, it will push $GOOGL to work with beta models rather than wait.
[Transcription] As mentioned, Alphabet is also on board ever since 2018. They have more than doubled their holdings in Gitlab in the past quarter, and thinking long-term, I think Alphabet may step up and purchase the whole company sooner or later.
⚡️@StockMKTNewz: "As of January 20, 2023, Google said that FDA approved pharmaceuticals that contain cannabidiol—as well as “topical, hemp-derived CBD products with THC content of 0.3 percent or less—can be advertised in those jurisdictions"
⚡️@googlecloud: This year, we worked with @SCJohnson’s repellent brand, @OFFoutdoors, to develop the OFF!Cast Mosquito Forecast—the world’s first public technology platform that predicts and shares mosquito population info up to 7 days in advance.
⚡️@TidefallCapital: "Paul Buchheit, the former Google employee who created Gmail, wrote in a series of posts on Twitter that (post ChatGPT) the company may be “only a year or two away from total disruption.” $GOOGL
⚡️@debarghya_das: 7/11 Should we use LLMs as Search oracles? Using LLMs directly drops the notion of provenance (where did this come from?) You cannot verify truths not attribute the falsety to anyone. It's non-deterministic as well. Google does not want to be liable for saying false things.
⚡️AI Supremacy: Google Issues "Code Red" Over ChatGPT: Google's management has reportedly issued a 'code red' amid the rising popularity of the ChatGPT AI
⚡️Surgehq.AI: We Evaluated ChatGPT vs. Google on 500 Search Queries
We measured ChatGPT vs. Google, and found that ChatGPT crushes Google on coding queries and ties it on general informational queries— despite not being optimized for a search experience at all. Dive into this post to learn more about OpenAI’s existential threat to Google.
⚡️@glengabe: As everyone focuses on OpenAI & GPT, Google is thinking a few steps ahead & acquiring a company building the host where AI tech could live (in a robot assistant) :) -> Alphabet’s Intrinsic acquires DARPA-backed firm behind open source robotics software
