Anthropic Co-Founder on New AI Models for Chatbot Claude
Summary
TLDRIn diesem Video geht es um die Ankündigung einer neuen Familie von Sprachmodellen von Anthropic, genannt „Claude 3". Die Modelle Claude 3 Opus, Claude 3 Sonet und Claude 3 Haiku sollen doppelt so leistungsfähig bei der Beantwortung von Fragen sein. Ein besonderer Fokus liegt auf der Integration dieser KI-Systeme in Unternehmen und deren Arbeitsabläufe, sowie auf Zuverlässigkeit, Sicherheit und Vertrauenswürdigkeit. Die Modelle sind für Geschäftskunden und den Endverbrauchermarkt erhältlich. Das Unternehmen strebt an, eine Vorreiterrolle bei sicheren und vertrauenswürdigen KI-Modellen einzunehmen und gleichzeitig deren Leistungsfähigkeit zu steigern.
Takeaways
- 🌟 Anthropic kündigt die Veröffentlichung der neuen Modell-Familie Claude 3 an, bestehend aus Claude 3 Opus, Claude 3 Sonnet und Claude 3 Haiku.
- 📈 Die neuen Modelle sind doppelt so wahrscheinlich, Fragen korrekt zu beantworten und bieten verbesserte Intelligenz und Leistung.
- 🔒 Einer der Hauptschwerpunkte von Anthropic ist die Bereitstellung sicherer, vertrauenswürdiger und zuverlässiger KI-Modelle durch die Verwendung von Constitutional AI.
- ⚡ Claude 3 Opus ist das leistungsstärkste Modell, Claude 3 Sonnet bietet ein gutes Preis-Leistungs-Verhältnis und Claude 3 Haiku ist sehr schnell.
- 🌐 Claude 3 Opus und Claude 3 Sonnet sind ab sofort über die Anthropic-API verfügbar, Claude 3 Haiku folgt in den kommenden Wochen.
- 🏢 Anthropic konzentriert sich auf die kommerzielle Nutzung und den Unternehmenseinsatz von KI, wobei Sicherheit und Vertrauen im Vordergrund stehen.
- 💼 Führende Unternehmen wie Bridgewater, SAP und Dana-Farber setzen bereits auf die KI-Modelle von Anthropic.
- 🔀 Es wird erwartet, dass Unternehmen einen Mehrmodell-Ansatz verfolgen und verschiedene KI-Modelle für unterschiedliche Anwendungsfälle einsetzen werden.
- 🌐 Anthropic vertritt die Auffassung, dass sowohl offene als auch geschlossene KI-Ansätze ihre Berechtigung haben und nebeneinander existieren können.
- 🔮 Als Public-Benefit-Unternehmen strebt Anthropic an, mit seiner KI das Leben der Menschen zu verbessern und einen positiven Einfluss auszuüben.
Q & A
Was bedeutet es, wenn gesagt wird, dass die neuen Modelle doppelt so wahrscheinlich eine Frage korrekt beantworten?
-Dies bezieht sich darauf, wie unwahrscheinlich es ist, dass eines dieser Modelle etwas erfindet oder ausdenkt. Die neuen Modelle wurden dahingehend verbessert, dass sie seltener falsche Informationen generieren.
Welche Modelle aus der Cloud-3-Familie werden derzeit angeboten?
-Zum jetzigen Zeitpunkt sind Cloud-3 Opus und Cloud-3 Sonet über die API von Anthropic verfügbar. Cloud-3 Haiku, das schnellste der drei Modelle, wird in den kommenden Wochen eingeführt.
Wo kann man auf Cloud-3 Sonet zugreifen?
-Cloud-3 Sonet ist heute über die Bedrock-Plattform von Amazon und in einer privaten Vorschau auf GCP Vertex von Google zugänglich.
Was zeichnet Cloud-3 Opus im Vergleich zu Konkurrenzprodukten aus?
-Cloud-3 Opus ist zwar relativ teuer, bietet aber branchenführende Leistung bei komplexen Denkaufgaben. Anthropic legt großen Wert darauf, dass ihre Modelle vertrauenswürdig und zuverlässig sind, was für viele Unternehmenskunden von großer Bedeutung ist.
Wie geht Anthropic mit potenziellen Sicherheitsbedenken und Verzerrungen in ihren Modellen um?
-Anthropic setzt die Technik der 'Constitutional AI' ein, die den Modellen eine Art 'Verfassung' für den Umgang mit heiklen Fragen mitgibt. Sicherheit und Vertrauenswürdigkeit haben für das Unternehmen höchste Priorität.
Wie reagiert Anthropic auf die Klage von Elon Musk gegen OpenAI und dessen Vorwurf, vom ursprünglichen gemeinwohlorientierten Auftrag abzuweichen?
-Anthropic betont, dass sie als Unternehmen für öffentliches Wohl den Spagat zwischen der Leistungsfähigkeit der KI und deren Sicherheit und Vertrauenswürdigkeit bewältigen wollen. Ihre Gründungsvision war es, Maßstäbe in der KI-Branche für Sicherheit zu setzen.
Wie vereinbart Anthropic kommerzielle Ziele mit seiner Mission für das öffentliche Wohl?
-Laut Anthropic sind Sicherheit, Vertrauenswürdigkeit und Zuverlässigkeit ein großer Anreiz für Unternehmenskunden, die auf Vertrauen bei ihren Kunden angewiesen sind. Das Unternehmen sieht die Bereitstellung sicherer KI-Systeme als im Einklang mit seiner Mission des öffentlichen Wohls.
In welchen Branchen setzen Kunden bereits Anthropics KI-Modelle ein?
-Kunden aus Finanzdienstleistungen, Telekommunikation, Bildung, Gesundheitswesen und Nonprofit-Organisationen setzen die KI-Modelle von Anthropic bereits ein, darunter namhafte Unternehmen wie Bridgewater, SAP und das Dana-Farber Cancer Institute.
Wie positioniert sich Anthropic in der Debatte um offene vs geschlossene KI-Systeme?
-Anthropic ist der Ansicht, dass es in der KI-Branche Platz für verschiedene Ansätze gibt. Viele Unternehmen werden voraussichtlich einen Multi-Modell-Ansatz verfolgen und für unterschiedliche Anwendungsfälle verschiedene KI-Systeme nutzen.
Welche Rolle spielt Geschwindigkeit bei der Cloud-3-Modellreihe?
-Cloud-3 Haiku ist das schnellste der drei Modelle und eignet sich besonders für Anwendungsfälle, bei denen schnelle Reaktionszeiten erforderlich sind. Cloud-3 Sonet ist ebenfalls recht schnell bei immer noch hoher Leistungsfähigkeit.
Outlines
🤖 Vorstellung der neuen Claude-Modell-Familie und deren Fähigkeiten
In diesem Abschnitt werden die neuen leistungsstarken KI-Modelle von Anthropic vorgestellt. Die Modelle Claude 3 Opus, Claude 3 Sonet und Claude 3 Haiku werden mit ihren jeweiligen Stärken und Anwendungsbereichen erläutert. Ein Fokus liegt auf der erhöhten Zuverlässigkeit, Sicherheit und Vertrauenswürdigkeit der Modelle, die für den Unternehmenseinsatz von großer Bedeutung sind. Die sofortige Verfügbarkeit der Modelle über verschiedene Plattformen wird ebenso angesprochen.
🔍 Erläuterung des Ansatzes von Anthropic zu Sicherheit, Vertrauen und offenen vs. geschlossenen KI-Systemen
Dieser Teil behandelt Anthropics Herangehensweise an Sicherheit, Vertrauenswürdigkeit und Ethik bei der Entwicklung von KI-Systemen. Die Verwendung von 'Constitutional AI' zur Berücksichtigung schwieriger ethischer Fragen wird erläutert. Die Rechtsstreitigkeiten zwischen Elon Musk und OpenAI werden kurz angesprochen, ebenso wie Anthropics Position als 'Public Benefit Corporation'. Der Schwerpunkt liegt auf dem Ausgleich zwischen leistungsstarken KI-Systemen und der Gewährleistung von Sicherheit und Vertrauen, insbesondere für Unternehmenskunden. Die Debatte um offene vs. geschlossene KI-Systeme wird diskutiert, wobei Anthropic einen Mehrwert in der Koexistenz verschiedener Ansätze sieht.
Mindmap
Keywords
💡Modell-Familie
💡Zuverlässigkeit
💡Kommerzielle Nutzung
💡Sicherheit
💡Öffentlicher Nutzen
💡Open vs. Closed AI
💡Leistungsfähigkeit
💡Geschwindigkeit
💡Unternehmensanforderungen
💡Verfassungs-KI
Highlights
Anthropic announced their new model family called Claude 3, which includes Claude 3 Opus (the most powerful state-of-the-art model), Claude 3 Sonnet (a capable and price-competitive middle model), and Claude 3 Haiku (a fast model for quick responses).
The models aim to have a higher likelihood of providing correct answers, rather than making something up.
Anthropic has been working on addressing common challenges that businesses and enterprises face when integrating generative AI into their workflows.
Claude 3 Opus and Claude 3 Sonnet are available immediately through Anthropic's API, with Claude 3 Haiku to be rolled out in the coming weeks.
Claude 3 Sonnet is also available on Anthropic's Bedrock platform and Google Cloud Platform's Vertex AI.
Anthropic's consumer product, Claude AI, offers access to Claude 3 Sonnet for free and Claude 3 Opus for paid users.
Anthropic's enterprise strategy focuses on building increasingly intelligent and fast models while prioritizing reliability and trustworthiness.
Anthropic uses a technique called Constitutional AI to provide their models with guidance on how to approach challenging questions and prompts.
As a public benefit corporation, Anthropic aims to balance the potential power of AI technologies with ensuring their reliability and safety.
Anthropic's founding mission is to raise the industry standard for safe and capable AI models.
Anthropic sees their focus on safety and trustworthiness as a major draw for enterprise customers who prioritize trust with their consumers.
Anthropic's customers span various industries, including financial services, telecommunications, education, healthcare, and non-profits.
Anthropic believes there is space for different models and approaches in the generative AI industry, and businesses may take a multi-model approach using different models for different use cases.
Anthropic acknowledges the ongoing debate around open versus closed AI development approaches, but believes there is room for various players to operate in the generative AI space.
Anthropic's strategy involves offering a range of models to cater to different business needs, allowing customers to toggle between models based on their priorities (e.g., power, speed, or cost).
Transcripts
You're saying these models are twice as likely to answer a question correctly.
What do we mean by that? So, first of all, Ed, thank you so much
for for having me on the program today. We are very excited to be announcing
this new model family of of Claude three.
And really, when you say, you know, twice as likely to answer, you know,
correctly, what that means is how high or how likely is it that one of these
models will sort of make something up. And so in addition to making these kind
of intelligence advances really across all three models, we've also been
working on many of the common challenges that businesses and in particular
enterprises face when integrating generative AI into their businesses and
workflows. One computer scientist reached out to me
and said, Oh, I've never used Claude, but I'm impressed by the testing scores,
but also impressed by the fact that it's available straight away.
And I also note that Amazon came out very quick to say, Go to bedrock.
You can use it right now. Bedrock has been a real success for you
guys in commercially commercializing the underlying models.
Just explain the rollout and how you're able to do this immediately.
So what's being offered today? So you mentioned those three.
There's three models in the family. So Cloud three Opus is really our most
powerful state of the art model. Cloud three Sonet is that middle model
that is still incredibly capable and quite price competitive, particularly
for its intelligence class and very fast.
And then Cloud three Haiku is the kind of fastest model really, really great
for sort of, you know, any type of use case that requires a quick response.
And so today what's available in our API is cloud ops and cloud sonnet.
So the bigger two models, Cloud three haiku will be rolled out in the coming
weeks. And then on us bedrock, you can access
Clod sonnet, that middle model today. And also on GCP vertex in private
preview you can also access clouds on it.
And I'd be remiss to not mention Claudia AI, our consumer consumer product.
You can access clouds on it for free, and cloud ops is available for our
producers as well. But you know, what's been interesting
about the focus that you've had at ANTHROPIC is on the commercial use is on
the business case use and I'm interested it is Opus is relatively expensive
compared to some of the competitors out there.
What is what your client base drawn to? Is it still the focus on safety, which
was first and foremost, or what else are you winning them on over the
competition? So really the kind of reasoning behind
why we did this model family was we wanted to give enterprise businesses as
much choice as possible to really be able to toggle between what is the most
important kind of element for their business or even in particular for for
their use cases. We anticipate some of our customers may
use, you know, multiple models just for different applications.
So, you know, Quad three Opus is really a great choice if you're if you need the
kind of most powerful state of the art model for very complex reasoning.
And I also should say so much of our enterprise kind of strategy has been
around building these models and making them increasingly more intelligent and
and fast, but really also ensuring that throughout we are prioritizing
reliability and trustworthiness. So many of the businesses that we build
on, that build on quad, you know, really require a deep amount of trust with the
customers that they're ultimately building for.
And that's really been kind of a guiding factor for us as we have been training
these models for our customers. And that goes straight to the heart of
some of the difficulties that have consumed your competitors and just
general adoption of AI within the landscape from a regulatory perspective
and a consumer use point. I think of the image generation part of
the equation right now. We all look to what's happening with
Gemini and the fact that they try to alleviate the bias issues and in so
doing ended up with a historical images. Talk us through some of the ways in
which you get over the hurdles of trying to put safety first, of trying to put
bias first, but trying to get these ultimately incredibly powerful models
into people's hands quickly. So one of the things that we have always
really focused on from day one is this question around safety and
trustworthiness and reliability. And while it's the case that, you know,
no model available on the market today is perfect, Anthropic has always really
aimed to be the industry leader when it comes to safety.
We use a technique called constitutional AI, which helps to provide all of our
models, including the Cloud three model family, with this sort of constitution
for how to approach, you know, challenging questions, right?
Introducing a sort of layer of nuance into how the models might respond to two
difficult prompts. Daniela you and many of your
co-founders, Entropic, previously worked at Openai.
Elon Musk has sued Open Air and is saying basically that breaching their
original contracts because they are no longer a not for profit and they are not
following that original mission of benefiting humanity through that work.
Your reaction to that, given your history?
Open our eye, but also the work you're doing now at ANTHROPIC, which has a
similar not for profit set up. So something that we've always aimed to
do as as a public benefit corporation at ANTHROPIC is really, you know, balance
the kind of incredible potential power of these technologies while still
ensuring that what we're developing is reliable and safe and really our kind of
founding vision. Right?
Our founding mission for the company was let's work to really raise the watermark
in the industry of AI and ensure that whenever we put a model on the market,
Anthropic wants to feel very confident that it is as safe as it as it can be.
And I think what has been so exciting I think about this model release is really
raising that water mark not just on safety, but also on intelligence and
capability simultaneously. And I think that Guiding Light has
always been an incredibly sort of important founding principle for us.
Caroline mentioned it, and you and I have talked about it, that you're you're
pursuing a focus on enterprise customers, you know, SAS cloud
companies, but you still have this public benefit call
center. Just explain how you manage both of
those goals. So something that I think is really
interesting that we've seen with, you know, so many of the enterprise
businesses that are really, you know, building on top of Clyde is that this
approach to building systems that are, you know, safe and kind of built on on
trust and are secure and are reliable is actually a huge draw for them.
Right. So many of the Fortune 500 are driven
really by trust with their with their consumers.
Right. And so I think something we take
incredibly seriously is this belief that when we are helping to to empower
businesses to build on cloud, that what we're putting in front of them is safe.
And I think that's perfectly in line with our public benefit mission.
Are you ultimately improving people's lives?
Do you still feel, Daniella, you as a company but as an industry more broadly?
So something we've been really kind of excited and inspired to see are just the
incredible potential and kind of use cases that our customers are using while
interacting with cloud. So this ranges from things like.
Financial services businesses like Bridgewater and SAP.
Telecom really just transforming how they work and how they interact with
with their end customers. But, you know, most recently I think
I've been incredibly excited to see so many, you know, education, health care
and non-profit businesses as well, really start to take on kind of the
mantle of generative AI. We've been very excited that that groups
like the Dana-Farber Cancer Institute are building on Clyde's.
So, too is a saw on a table. Bridgewater some really notable names in
the finance space and in productivity space.
And I'm interested that at the time that clearly from an enterprise perspective,
everyone's rushing to get in and clearly productivity can go up and to the right
to a significant amount. We do question perhaps some worries
around jobs, but we also question ultimately open AI versus closed AI.
And we go back a little bit to the drama that's unfolding between Elon Musk and
Openai. And I know you must be relatively
exhausted by that. But I look at what's been noted.
Kozol, for example, has been tweeting about saying that ultimately Sam Gregg
and the team over and over have been pushing out foster better products, and
they need to be in a more closed space, open A.I.
And ultimately, artificial intelligence innovation shouldn't be done permanently
in some sort of open test way and means of doing it.
Do you agree? What is your ethos on open versus closed
on? I think really bottom line is that
there's so much space in the kind of generative AI industry, right?
There are many different types of models that are being rolled out across really
a variety of different services. And my sense is that as businesses
really are becoming quite sophisticated with how they integrate these generative
AI technologies, I expect that what we'll see is really a kind of
multi-model approach that many businesses might choose to rely on one
type of model for certain use cases and other types of models for others.
So I feel there's really quite a lot of sort of space and territory for all of
these different players to kind of operate in the space.
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