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Sources say General Catalyst is working on a “follow-on” fund worth up to $1 billion

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Hemant Taneja, Managing Partner, General Catalyst

General Catalyst, certainly one of Silicon Valley’s largest enterprise capital firms, is preparing to launch a so-called “follow-on fund” worth between $800 million and $1 billion, according to a person conversant in the plans.

The follow-on fund consists of a portion of the shares that the VC firm holds in portfolio firms. From approx $25 billion by way of assets under management for 2023, the precise composition of General Catalyst’s follow-on fund portfolio is still being determined. However, it’s going to likely take stakes in Stripe, Gusto and Circle, the person added. The company recently hired Jefferies as a further investment advisor.

Once the fund is created and investors are found for it, General Catalyst’s original limited partners could have a alternative: sell their shares and money out, making room for brand new investors, or remain invested within the follow-on fund (a process called “rolling”). ‘

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Although private equity firms have long used follow-on funds, this mechanism has only recently gained popularity amongst enterprise capitalists, largely due to the low variety of IPOs and slowing M&A activity. This has forced some large enterprise capital firms to use the secondary market to return capital to their limited partners.

In July, for instance, Bloomberg reported that NEA sold shares in 11 portfolio firms, including Databricks and Plaid, to secondary investors who collectively paid $540 million for assets. Lightspeed is currently within the technique of selling a group of existing businesses valued at as much as $1 billion to used buyers.

Like NEA and Lightspeed, General Catalyst’s follow-on fund will consist of late-stage startups which have increased in value for the reason that company first invested within the asset.

General Catalyst didn’t respond to a request for comment.

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The primary advantage of a follow-on fund, as opposed to simply selling the shares to one other buyer in a secondary market transaction, is that it allows VC investors to proceed to manage the shares while retaining any future advantages from them. Follow-on funds are also considered more founder-friendly than secondary sales of shares of individual startups because they don’t introduce latest owners into the startup capitalization table. The same VC fund stays invested, albeit through a different fund.

VC funds have been more willing to sell on secondary markets currently as some LPs tell them they’ll reduce on their investments in one other VC fund in the event that they don’t receive at the least a few of the money returns on older investments.

While follow-on funds are generally useful to enterprise capital funds, they will pose a conundrum for some limited partners. Because secondary partnerships sell stock at a significant discount to current valuations – typically 20% to 30% from current valuations – when selling shares, limited partners cannot only take a haircut to existing valuations, but additionally forgo potential increases in stock prices.

Still, one General Catalyst limited partner told TechCrunch that given the shortage of liquidity from enterprise capital investments, his pension fund would at all times select to money out reasonably than move into a follow-on fund.

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The person didn’t say when this LP would receive this chance, and Top Contributor is unable to estimate this. Follow-on funds are complex transactions that may take anywhere from six months to a 12 months to sell. These transactions may additionally fail completely. Last 12 months, Tiger Global tried to sell a sort of follow-on fund called a strip portfolio, which sells only a portion of its holdings in each company. However, it couldn’t find a buyer willing to pay a price that the corporate considered fair, PitchBook reported.

When Shasta Ventures asked its limited partners earlier this 12 months to approve a follow-on fund that was valued at 35% below carrying value, the corporate’s investors voted against the deal, – Axios reported.
In April, the Financial Times reported that General Catalyst would commit capital worth almost $6 billion to the brand new core fund. The latest fund has still not been announced. When TechCrunch asked for more details about its fundraising efforts last week, the corporate declined to comment.

This article was originally published on : techcrunch.com
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Claude: Everything you need to know about AI Antropic

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Anthropic Claude 3.5 logo

Anthropic, one in every of the world’s largest artificial intelligence suppliers, has a strong family of generative AI models called Claude. These models can perform quite a few tasks, from painting signatures and writing E -Mail to solving mathematical challenges and coding.

Because the anthropic model is growing so fast, it’s difficult to follow which Claude models do it. To help, we’ve got developed a Claude guide, which we shall be up to date when latest models and updates come.

Claude models

Claude models are named after literary artworks: Haiku, Sonnet and Opus. The latest are:

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  • Claude 3.5 haikulight model.
  • SONET CLAUDE 3.7Hybrid, medium, hybrid reasoning model. This is currently the flagship model of AI Anthropika.
  • Close the third jobLarge model.

It is needed, Claude 3 Opus – the biggest and most costly anthropic model of offers – is currently the least capable Claude model. This definitely changes when Anthropic releases an updated version of Opus.

Recently, Anthropic has released Sonnet Claude 3.7, probably the most advanced model. This AI model differs from Claude 3.5 Haiku and Claude 3 Opus, since it is a hybrid model of AI reasoning, which might give each real -time answers and more thoughtful answers to questions.

Using Claude 3.7 Sonnet, users can select whether to include the flexibility to reason the AI ​​model, which prompts the model to “think” for a brief or long period.

When the reasoning is turned on, the Claude 3.7 sonnet will spend from a couple of seconds to a couple of minutes within the “thinking” phase before the reply. During this phase, the AI ​​model spreads the user’s prompt into smaller parts and checks its answers.

Sonet Claude 3.7 is the primary AI model that may “reason”, a way to which many AI laboratories turned to traditional methods of improving the cone of artificial intelligence.

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Even with disabled reasoning, Claude 3.7 Sonnet stays one in every of the very best models of the technology industry.

In November, Antropic released an improved – and dearer – version of its light model AI, Claude 3.5 Haiku. This model exceeds Opus Claude 3 Anthropica on several comparative tests, but cannot analyze images similar to Claude 3 Opus or Claude 3.7 Sonnet.

All Claude-which models have a typical contextual window of 200,000-year-old-also follow multi-stage instructions, Use tools (e.g. Ticker Ticker Json.

The context window is the quantity of information that a model similar to Claude can analyze before generating latest data, while tokens are divided by bits of raw data (similar to the syllables “fan”, “tas” and “tic” within the word “fantastic”). Two hundred thousand tokens are equivalent to about 150,000 words or a 600-page novel.

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Unlike many primary generative AI models, Anthropic cannot access the Internet, which implies that they will not be particularly great in answering current questions. They also cannot generate images – only easy line schemes.

As for the primary differences between Claude models, the Claude 3.7 sonet is quicker than Claude 3 Opus and understands higher refined and complicated instructions. Haiku struggles with sophisticated hints, but that is the fastest of three models.

Deliberate prices of the Claude model

Claude models can be found via API Antropic and managed platforms, similar to Amazon Bedrock and Google Cloud Vertex AI.

Here are anthropic API prices:

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  • Claude 3.5 haiku It costs 80 cents for million input tokens (~ 750,000 words) or 4 USD production tokens for 1,000,000
  • SONET CLAUDE 3.7 costs $ 3 for a million input tokens or USD 15 per million tokens
  • Close the third job It costs USD 15 per million tokens or USD 75 for a million production tokens

Anthropic offers fast buffering and parties to get additional savings through the performance.

Fast buffering allows programmers to store specific “fast contexts”, which could be reused in API connections for the model, and asynchronous group processes groups with low priority (after which cheaper) demands of the model’s request.

Claude plans and applications

For individual users and corporations that simply want to interact with Claude models via applications for the Internet, Android and iOS, Antropic offers a free Claude plan with rate limitations and other restrictions on use.

The update to one in every of the corporate’s subscriptions removes these limits and unlocks latest functionality. Current plans are:

Claude Pro, which costs $ 20 a month, has 5 times higher rate limits, priority access and preview of the upcoming functions.

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A business-oriented team costs 30 USD per month-adds navigation desktop to control the invoicing and management of users, and integration with data repositors similar to code databases and customer relationship management platforms (e.g. Salesforce). The switch allows or turns off quotes of verification of claims generated by AI. (Like all models, Claude from time to time hallucinates.)

Both subscribers of pros and the team receive projects, a function that relies on Claude leads to knowledge databases, which could be stylish guides, intelligence transcripts and so forth. These customers, along with free level users, may use artifacts, a working area where users can edit and add to content similar to code, applications, web sites and other documents generated by Claude.

For customers who need much more, there may be Claude Enterprise, which allows firms to send reserved data to Claude in order that Claude can analyze information and answer questions. Claude Enterprise also has a bigger context window (500,000 tokens), GitHub integration for engineering teams to synchronize their GitHub repositories with Claude in addition to projects and artifacts.

Caution

As with all AI generative models, there may be a risk related to using Claude.

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Models sometimes Make mistakes through the summary Or Answering the questions Because of their tendency to hallucination. They are also trained in public web data, a few of which could also be protected by copyright or under a restrictive license. Anthropic and plenty of other AI suppliers claims that honest use The doctrine protects them against copyright claims. But this didn’t stop the info owners With Folding processes.

Anthropic offers rules To protect some clients from the battles of the courtroom resulting from challenges regarding honest use. However, they don’t solve the moral breakup of using models trained on the idea of information without permission.


(Tagstranslatate) AI (T) Anthropic

This article was originally published on : techcrunch.com
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A single default slogan reveals access to dozens of residential buildings

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a door entry system on the front of a residential building, illustrated for the story

The safety researcher claims that the default password sent within the widely used door access control system allows everyone to easily and remotely access the door locks and inspection of elevators in dozens of buildings within the USA and Canada.

Hirsch, an organization that’s now the owner of the Enterphone Mesh door access system is not going to fix the gap, saying that the error is according to the design and that customers should follow the corporate’s configuration instructions and alter the default password.

This leaves dozens of unveiled residential and office buildings in North America, which haven’t yet modified the default password of the access control system or usually are not aware that they need to, According to Eric Daiglewho found dozens of exposed buildings.

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The default slogans usually are not unusual or not necessarily a secret in devices connected to the Internet; Passwords supplied with products are frequently designed to simplify access to login for the shopper and are sometimes within the user manual. But counting on the client by changing the default password to prevent future malicious access it still classifies as susceptibility to security within the product itself.

In the case of Hirsch door products, customers usually are not monitored or required to change the default password.

As such, Daigle received a security error, formally marked as CVE-2025-26793.

No planned amendment

The default passwords have long been an issue for devices connected via the Internet, enabling malicious hackers to use passwords to log in as in the event that they were a legitimate owner and steal data or take over devices to use the bandwidth to introduce cyber attacks. In recent years, governments have tried to stop technology producers from the use of uncertain default slogans, making an allowance for the chance of security.

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In the case of the Hirsch door entry system, the error is rated as 10 out of 10 on a severity of susceptibility, thanks to the benefit with which everyone can use it. Practically speaking, the use of an error is so simple as taking the default password from the system’s installation guide on the Hirsch website and connecting the password to the login page addressed to the Internet within the system of any constructing.

IN Blog postDaigle said that last yr he was susceptible after discovering one of the doorway panels to the Enterphone door in Hirsch in a constructing within the hometown of Vancouver. Daigle used the Zoomeye scanning website to seek for Enterphone network systems that were connected to the Internet, and located 71 systems that were still based on unconnected obligations.

Daigle said that the default password allows access to the net Mesh background system, whose constructing managers use to manage access to winds, common areas and office and housing locks. Each system displays the physical address of the constructing with the mesh system installed, enabling everyone to whose constructing they’ve access.

Daigle said that you would be able to effectively break into dozens of affected buildings inside just a few minutes without attracting attention.

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TechCrunch intervened because Hirsch has no funds reminiscent of the revelation of sensitivity, members of society reminiscent of Daigle reported a security defect to the corporate.

Mark Allen, general director of Hirsch, didn’t answer Techcrunch’s request for commentary, but as an alternative put down his senior Hirsch product manager, who told Techcrunch that the use of default passwords by the corporate is “outdated” (regardless of how). The product manager said that “is equally worrying”, that there are customers who “installed systems and do not comply with manufacturers’ recommendations”, referring to their very own instructions for the Hirsch installation.

Hirsch wouldn’t commit himself to publicly disclose the main points in regards to the error, but said that he had contacted his clients regarding tracking the product manual.

Because Hirsch doesn’t want to fix the error, some buildings – and their inhabitants – will probably remain exposed. The error shows that selections regarding product development from the past can come back to have implications in the true world summer later.

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(Tagstranslata) cyber security

This article was originally published on : techcrunch.com
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Did Xai lie about GROK 3 comparative tests?

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The xAI Grok AI logo

Debates on AI comparative tests – and their reporting by AI Labs – spill at the general public.

This week, Openai worker accused Elon Musk’s Ai Company, XAI, publishing comparative results for his or her latest AI model, Grok 3. One of the co -founders of XAI, Igor Babushkin, he insisted that the corporate had the suitable.

The truth lies somewhere in between.

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IN Publish on the XAI blogThe company has published a chart showing the outcomes of GROK 3 on Aime 2025, a set of adverse mathematical questions from the recent Invitational mathematical exam. Some experts have Aime validity as a AI reference point. Nevertheless, AIME 2025 and older versions of the test are widely used to look at the mathematical ability of the model.

The XAI chart showed two variants of GROK 3, Grok 3 Reasoning Beta and GroK 3 mini reasoning, beating the very best available OpenAI, O3-Mini-High, on Aime 2025. But OpenAI employees on X quickly noticed that the XAI chart XAI chart. He didn’t consider the AME 2025 O3-Mini-High lead to “Cons@64”.

What is Cons@64, are you able to ask? Well, that is the abbreviation for “Conszeus@64” and principally gives model 64 tries to reply every problem in relation and accepts answers most frequently generated as final answers. As you may imagine, Cons@64 tends to extend the outcomes of the models, and skipping it from the chart may cause one model to surpass one other when it shouldn’t be in point of fact.

GROK 3 Beta and grok 3 mini reasoning for AIME 2025 at “@1”-what implies that the primary result, which models have achieved at a distance-see below the results of the O3-Mini-High. Grok 3 Reasoning Beta also the trail also behind the O1 Openai model on “Medium” Computing. However, XAI is GROK 3 promoting As “the smartest artificial intelligence of the world.”

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Babushkin Ox was arguing that OpenAI previously published similarly misleading comparative charts – although charts comparing the performance of its own models. A more neutral event in the talk has developed a more “accurate” chart showing almost every model in Cons@64:

But as a researcher AI Nathan Lambert He identified within the postPerhaps crucial metric stays a secret: the calculation (and money) cost he needed for every model to realize his best result. It simply shows how little a lot of the test tests AI communicates about the restrictions of models – and their strengths.

(Toshma of All State) (Enter updates) in Triptaren !!!

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This article was originally published on : techcrunch.com
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