Monthly Archives: May 2023

Stability AI is releasing an open-source version of DreamStudio, a commercial interface for the companys AI image generator model, Stable Diffusion. In a press statement on Wednesday, Stability AI said the new release dubbed StableStudio marks a fresh chapter for the platform and will serve as a showcase for the companys dedication to advancing open-source development.

Making an open-source version of DreamStudio carries benefits for Stability AI. It allows community developers to improve and experiment with the interface, with the company potentially reaping the rewards conferred by these improvements. Stability AI stressed community building in its press release, noting how from enabling local-first development, to experimenting with a new plugin system, weve tried hard to make things extensible for external developers.

Stability AIs approach to open-source development has helped drive interest in its products

Stability AI has previously leaned hard on its open-source approach to create interest in its products. Various versions of Stable Diffusion have been freely available to download and tinker with since the model was publicly released back in August 2022, and last month, the company released a suite of open-source large language models (LLMs) collectively called StableLM. Stability AIs founder and CEO, Emad Mostaque, has been outspoken about the importance of making AI tools open source in order to increase public trust, claiming that open models will be essential for private data, in a Zoom call with the press last month.

However, the companys approach sometimes seems to lack direction, too. For example, StableStudio will be available alongside DreamStudio and potentially compete with it. The company has previously said it plans to generate revenue by creating customized versions of DreamStudio for corporate clients, but its not clear how successful this strategy has been. Recent reports suggest the firm is burning through cash and note that its most important models, like Stable Diffusion, were built in collaboration with other parties.

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Stability AI releases StableStudio in latest push for open-source AI - The Verge

Companies across industries are using artificial Intelligence (AI). And that has people thinking about what AI means for the future of many professions. Alphabet (GOOG 1.16%) (GOOGL 1.11%), the parent company of Google, is no stranger to AI. The company uses AI throughout its business -- from optimizing its search capabilities to better serving its advertising customers.

Recently, Alphabet chief executive officer Sundar Pichai spoke about how AI is set to revolutionize the working world. He even said one industry in particular might be transformed by the technology. And, surprisingly, Pichai says this may not result in layoffs -- but instead, more jobs.

Pichai told The Verge in an interview that AI may make the law profession better in certain ways and may result in more people actually becoming lawyers. Law firms today already use AI to help draft documents, verify contracts, and complete other tasks. The idea is AI won't take away lawyers' jobs. Instead, it will help them and their staff do certain things more quickly -- and give them more time to focus on more complicated parts of the job.

"I'm willing to almost bet 10 years from now, maybe there are more lawyers," Pichai said in the interview.

Pichai said that some of the jitters people have about AI today are a lot like the worries they had years ago with the introduction of new technology like computers or the Internet. Yes, these technologies may have hurt some jobs, but they've also introduced many new ones and resulted in overall progression in the employment market.

Pichai is doing his part to advance the use of AI. He's made it a focus at Alphabet. For instance, the company uses it to help the Google search engine better understand the meaning of each vocal and written search. Another example, this time in the area of advertising: An AI tool predicts how much advertisers should spend to meet their campaign goals.

So, the use of AI isn't necessarily about eliminating jobs. It's about improving how we do them. And this makes AI a great new technology to invest in today. Alphabet itself is a solid AI stock to buy -- and investors will like the company for other reasons too, such as its giant market share in the search market. Google Search holds 92% of that market. And its use of AI may keep that going.

You also can invest in AI by buying shares of e-commerce giant Amazon (AMZN 1.85%). The company has used AI for years -- that's what helps Amazon recommend products to you that you may like, for example. And last year, Amazoneven bought a company called Snackable.AI. Amazon intends to use the company's machine learning tools to boost its streaming and podcast capabilities.

But AI isn't limited to tech companies. You'll find companies in healthcare turning their attention to the area too. Vaccine maker Moderna (MRNA 0.37%) used AI to help it in the development of the coronavirus vaccine -- and is using it to make research and development more efficient. Moderna even recently signed a deal with International Business Machines to use that company's AI platform in the drug development process. And Medtronic is using AI in many ways, such as predicting outcomes in spine surgery.

That means there are plenty of stocks today offering you opportunities for AI investing. So, this technology may transform jobs -- as Pichai says -- and it may also open the door to new investment possibilities.

Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Adria Cimino has positions in Amazon.com. The Motley Fool has positions in and recommends Alphabet and Amazon.com. The Motley Fool recommends Moderna. The Motley Fool has a disclosure policy.

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Google CEO Sundar Pichai Predicts That This Profession Will Be ... - The Motley Fool

Frances privacy watchdog, the CNIL, has published an action plan for artificial intelligence which gives a snapshot of where it will be focusing its attention, including on generative AI technologies like OpenAIs ChatGPT, in the coming months and beyond.

A dedicated Artificial Intelligence Service has been set up within the CNIL to work on scoping the tech and producing recommendations for privacy-friendly AI systems.

A key stated goal for the regulator is to steer the development of AI that respects personal data, such as by developing the means to audit and control AI systems to protect people.

Understanding how AI systems impact people is another main focus, along with support for innovative players in the local AI ecosystem which apply the CNILs best practice.

The CNIL wants to establish clear rules protectingthe personal data of European citizens in order to contribute to the development of privacy-friendly AI systems, it writes.

Barely a week goes by without another bunch of high profile calls from technologists asking regulators to get to grips with AI. And just yesterday, during testimony in the US Senate, OpenAIs CEO Sam Altman called for lawmakers to regulate the technology, suggesting a licensing and testing regime.

However data protection regulators in Europe are far down the road already with the likes of Clearview AI already widely sanctioned across the bloc for misuse of peoples data, for example. While the AI chatbot, Replika, has faced recent enforcement in Italy.

OpenAIs ChatGPT also attracted a very public intervention by the Italian DPA at the end of March which led to the company rushing out with new disclosures and controls for users, letting them apply some limits on how it can use their information.

At the same time, EU lawmakers are in the process of hammering out agreement on a risk-based framework for regulating applications of AI which the bloc proposed back in April 2021.

This framework, the EU AI Act, could be adopted by the end of the year and the planned regulation is another reason the CNIL highlights for preparing its AI action plan, saying the work will also make it possible to prepare for the entry into application of the draft European AI Regulation, which is currently under discussion.

Existing data protection authorities (DPAs) are likely to play a role in enforcement of the AI Act so regulators building up AI understanding and expertise will be crucial for the regime to function effectively. While the topics and details EU DPAs choose focus their attention on are set to weight the operational parameters of AI in the future certainly in Europe and, potentially, further afield given how far ahead the bloc is when it comes to digital rule-making.

On generative AI, the French privacy regulator is paying special attention to the practice by certain AI model makers of scraping data off the Internet to build data-sets for training AI systems like large language models (LLMs) which can, for example, parse natural language and respond in a human-like way to communications.

It says a priority area for its AI service will be the protection of publicly available data on the web against the use of scraping, or scraping, of data for the design of tools.

This is an uncomfortable area for makers of LLMs like ChatGPT that have relied upon quietly scraping vast amounts of web data to repurpose as training fodder. Those that have hoovered up web information which contains personal data face a specific legal challenge in Europe where the General Data Protection Regulation (GDPR), in application since May 2018, requires them to have a legal basis for such processing.

There are a number of legal bases set out in the GDPR however possible options for a technology like ChatGPT are limited.

In the Italian DPAs view, there are just two possibilities: Consent or legitimate interests. And since OpenAI did not ask individual web users for their permission before ingesting their data the company is now relying on a claim of legitimate interests in Italy for the processing; a claim that remains under investigation by the local regulator, Garante. (Reminder: GDPR penalties can scale up to 4% of global annual turnover in addition to any corrective orders.)

The pan-EU regulation contains further requirements to entities processing personal data such as that the processing must be fair and transparent. So there are additional legal challenges for tools like ChatGPT to avoid falling foul of the law.

And notably in its action plan, Frances CNIL highlights the fairness and transparency of the data processing underlying the operation of [AI tools] as a particular question of interest that it says its Artificial Intelligence Service and another internal unit, the CNIL Digital Innovation Laboratory, will prioritize for scrutiny in the coming months.

Other stated priority areas the CNIL flags for its AI scoping are:

Giving testimony to a US senate committee yesterday, Altman was questioned by US lawmakers about the companys approach to protecting privacy and the OpenAI CEO sought to narrowly frame the topic as referring only to information actively provided by users of the AI chatbot noting, for example, that ChatGPT lets users specify they dont want their conversational history used as training data. (A feature it did not offer initially, however.)

Asked what specific steps its taken to protect privacy, Altman told the senate committee: We dont train on any data submitted to our API. So if youre a business customer of ours and submit data, we dont train on it at all If you use ChatGPT you can opt out of us training on your data. You can also delete your conversation history or your whole account.

But he had nothing to say about the data used to train the model in the first place.

Altmans narrow framing of what privacy means sidestepped the foundational question of the legality of training data. Call it the original privacy sin of generative AI, if you will. But its clear that eliding this topic is going to get increasingly difficult for OpenAI and its data-scraping ilk as regulators in Europe get on with enforcing the regions existing privacy laws on powerful AI systems.

In OpenAIs case, it will continue to be subject to a patchwork of enforcement approaches across Europe as it does not have an established base in the region which the GDPRs one-stop-shop mechanism does not apply (as it typically does for Big Tech) so any DPA is competent to regulate if it believes local users data is being processed and their rights are at risk.So while Italy went in hard earlier this year with an intervention on ChatGPT that imposed a stop-processing-order in parallel to it opening an investigation of the tool, Frances watchdog only announced an investigation back in April, in response to complaints. (Spain has also said its probing the tech, again without any additional actions as yet.)

In another difference between EU DPAs, the CNIL appears to be concerned about interrogating a wider array of issues than Italys preliminary list including considering how the GDPRs purpose limitation principle should apply to large language models like ChatGPT. Which suggests it could end up ordering a more expansive array of operational changes if it concludes the GDPR is being breached.

The CNIL will soon submit to a consultation a guide on the rules applicable to the sharing and re-use of data, it writes. This work will include the issue of re-use of freely accessible data on the internet and now used for learning many AI models. This guide will therefore be relevant for some of the data processing necessary for the design of AI systems, including generative AIs.

It will also continue its work on designing AI systems and building databases for machine learning. These will give riseto several publications starting in the summer of 2023, following the consultation which has already been organised with several actors, in order to provide concrete recommendations, in particular as regards the design of AI systems such as ChatGPT.

Heres the rest of the topics the CNIL says will be gradually addressed via future publications and AI guidance it produces:

On audit and control of AI systems, the French regulator stipulates that its actions this year will focus on three areas: Compliance with an existing position on the use of enhanced video surveillance, which it published in 2022; the use of AI to fight fraud (such as social insurance fraud); and on investigating complaints.

It also confirms it has already received complaints about the legal framework for the training and use of generative AIs and says its working on clarifications there.

The CNIL has, in particular, received several complaints against the company OpenAI which manages the ChatGPT service, and has opened a control procedure, it adds, noting the existence of a dedicated working group that was recently set up within the European Data Protection Board to try to coordinated how different European authorities approach regulating the AI chatbot (and produce what it bill as a harmonised analysis of the data processing implemented by the OpenAI tool).

In further words of warning for AI systems makers who never asked peoples permission to use their data, and may be hoping for future forgiveness, the CNIL notes that itll be paying particular attention to whether entities processing personal data to develop, train or use AI systems have:

As for support for innovative AI players that want to be compliant with European rules (and values), the CNIL has had a regulatory sandbox up and running for a couple of years and its encouraging AI companies and researchers working on developing AI systems that play nice with personal data protection rules to get in touch (via ia@cnil.fr).

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Frances privacy watchdog eyes protection against data scraping in AI action plan - TechCrunch

Solving consumer engagement is worth $1 trillion to our organization, said a health plan executive to me one day. He was obviously being a bit sensationalist with the magnitude of the number, but its been a common thread in strategic dialogue across all of healthcare for quite a whilethat so much of the high cost, waste, and poor clinical outcomes from which our healthcare system suffers stems from the lack of individuals engagement with itor the flip, which is healthcare organizations inability to engage, at scale and cost-effectively, with its patients and members.

And its not just consumer engagement that needs to be solvedour countrys severe clinician burnout problem, combined with overall high rates of staff churn, are causing healthcare organizations to falter at delivering on their core services. One study shows that the average hospital has turned over 100.5% of its workforce in the last 5 years!

In this context, when it comes to generative AI, healthcare is an industry that we view as holding the most potential for tangible and measurable impact. Closing the gap on a shortage of millions of healthcare workers in the next several years, while also trying to increase leverage for those already in the workforce, requires much more than just the traditional paths of training or importing more human labor. Were excited to be backing Hippocratic AI as they apply generative AI to execute against this opportunity set.

Imagine a world in which every patient, provider, and administrative staff member could interact with an immediately available, fully context-aware, completely capable, and charismatic conversationalist to help each individual pick the right path or do their job better (a form of always-on triage, as weve described in the past). Imagine that the marginal cost of engaging a patient through empathetic phone calls was on the order of $0.10 per hour, as opposed to the $50+ it might cost today. The very nature of generative AIconversational, scalable, accessible to non-technical usershas the potential to solve the shortcomings of previous generations of rules-based chatbots and other such products in making these concepts a reality.

But AI applications in healthcare also pose among the highest stakes of any industry. AI skeptics might point to the lack of focus on responsibility, safety, and regulatory compliance exhibited by many companies in this space. Not to mention the challenge of assembling a cross-disciplinary team with deep expertise in LLM development, healthcare delivery, and healthcare administration to build AI products that actually work.

Hippocratic AIs name alone represents their safety-first ethos (referring to the Hippocratic Oath that physicians commit to, in which the core principles are to do no harm to patients and to maintain confidentiality of a patients medical information). Theyve built a unique framework to incorporate professional-grade certification, RLHF (reinforcement learning from human feedback) through a panel of healthcare professionals, and bedside manner into their non-diagnostic, patient-facing conversational LLMs, with the recognition that passing a medical board exam is not enough to ensure that a model is ready to be deployed into a real-world setting.

Weve known the CEO, Munjal Shah, since investing in his last company in 2017 (which was his third, after previously selling an AI company to Google), and thus know he has uniquely earned secrets about how to build a company at the intersection of AI and healthcare. He most recently ran a Medicare brokerage business that involved a national-scale call center that made personalized recommendations to seniors based on their individual claims history. There, he led through the operational pains of scaling an empathetic but efficient engagement platform for consumers in a regulated healthcare context. We believe these competencies give him and his founding team (composed of individuals with clinical, LLM development, and healthcare operations experience) an edge in understanding what it takes to bring high-impact, responsible, and safe generative AI products to market, and consider it a privilege to be backing him again.

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Investing in Hippocratic AI - Andreessen Horowitz

Published: May 17, 2023 at 9:54 a.m. ET

A few months back, some on Wall Street were worried that Microsoft Corp.s artificial-intelligence advancements would help the company eat into Alphabet Inc.s dominant Google search business.

Those concerns may be soon fading, as the investment community has rightfully determined that Google is in good shape around AI, Barclays analyst Ross Sandler wrote in a note to clients Wednesday. But the search giant still faces other challenges as generative AI, the type of artificial intelligence popularized by ChatGPT, becomes...

A few months back, some on Wall Street were worried that Microsoft Corp.s artificial-intelligence advancements would help the company eat into Alphabet Inc.s dominant Google search business.

Those concerns may be soon fading, as the investment community has rightfully determined that Google is in good shape around AI, Barclays analyst Ross Sandler wrote in a note to clients Wednesday. But the search giant still faces other challenges as generative AI, the type of artificial intelligence popularized by ChatGPT, becomes more prominent.

See also: Google developers conference is all about AI

The new elephant in the room, in Sandlers view, is whether Alphabets GOOGL GOOG own efforts with AI end up hurting its big moneymaker, at least in the short term. The concern is that as Google integrates generative AI into its search business, people might start to get more information that way, rather than clicking through to revenue-generating sources like sponsored listings.

Its fairly well documented that the top position on legacy SERPs [search engine results pages] gets the lions share of the clicks, anywhere from 2% to 39% depending on whether the first link is an ad or an organic result, Sandler wrote.

So the obvious problem for Google is that mobile and desktop search engines powered by generative AI are a complete departure from the typical look of search, he continued. Not only is the percentage of screen real estate dedicated to ads much lower, the entire layout and flow of the SERP appears to be changing in many cases.

Read: Alphabet stock proves popular with big funds

He gave an example of a mobile search for house plants thats dominated by ads in its traditional form but devoid of any ads above the fold in the demo generative-AI search layout.

The point being that any movement of commercial query share toward less commercial share using GenAI, would have air-pocket impacts, Sandler wrote. This speaks to just how good a business model traditional search really is in many cases, the ads are just as relevant if not more relevant than the organic results.

On the bright side, Google has a history of finding new ways to monetize search, and Sandler thinks its possible that more relevant AI-driven answers could ultimately help click-through rates for top positions on the page.

An auction with a winner of one could actually monetize at or above the traditional 10-blue-link SERP, he wrote. But this is going to be a big unknown for the foreseeable future.

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As Alphabet flexes its AI prowess, there's a 'new elephant in the room' for Google - MarketWatch