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Google Gemini: everything you need to know about the new generative artificial intelligence platform

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Google is trying to impress with Gemini, its flagship suite of generative AI models, applications and services.

So what are Gemini? How can you use it? And how does it compare to the competition?

To help you sustain with the latest Gemini developments, we have created this handy guide, which we’ll keep updating as new Gemini models, features, and news about Google’s plans for Gemini grow to be available.

What is Gemini?

Gemini is owned by Google long promised, a family of next-generation GenAI models developed by Google’s artificial intelligence labs DeepMind and Google Research. It is available in three flavors:

  • Gemini Ultrathe best Gemini model.
  • Gemini Pro“lite” Gemini model.
  • Gemini Nanoa smaller “distilled” model that works on mobile devices like the Pixel 8 Pro.

All Gemini models were trained to be “natively multimodal” – in other words, able to work with and use greater than just words. They were pre-trained and tuned based on various audio files, images and videos, a big set of codebases and text in various languages.

This distinguishes Gemini from models akin to Google’s LaMDA, which was trained solely on text data. LaMDA cannot understand or generate anything beyond text (e.g. essays, email drafts), but this isn’t the case with Gemini models.

What is the difference between Gemini Apps and Gemini Models?

Image credits: Google

Google, proving once more that it has no talent for branding, didn’t make it clear from the starting that Gemini was separate and distinct from the Gemini web and mobile app (formerly Bard). Gemini Apps is solely an interface through which you can access certain Gemini models – consider it like Google’s GenAI client.

Incidentally, Gemini applications and models are also completely independent of Imagen 2, Google’s text-to-image model available in a few of the company’s development tools and environments.

What can Gemini do?

Because Gemini models are multimodal, they will theoretically perform a spread of multimodal tasks, from transcribing speech to adding captions to images and videos to creating graphics. Some of those features have already reached the product stage (more on that later), and Google guarantees that each one of them – and more – can be available in the near future.

Of course, it is a bit difficult to take the company’s word for it.

Google seriously fell in need of expectations when it got here to the original Bard launch. Recently, it caused a stir by publishing a video purporting to show the capabilities of Gemini, which turned out to be highly fabricated and kind of aspirational.

Still, assuming Google is kind of honest in its claims, here’s what the various tiers of Gemini will give you the option to do once they reach their full potential:

Gemini Ultra

Google claims that Gemini Ultra – thanks to its multimodality – may help with physics homework, solve step-by-step problems in a worksheet and indicate possible errors in already accomplished answers.

Gemini Ultra can be used for tasks akin to identifying scientific articles relevant to a selected problem, Google says, extracting information from those articles and “updating” a graph from one by generating the formulas needed to recreate the graph with newer data.

Gemini Ultra technically supports image generation as mentioned earlier. However, this feature has not yet been implemented in the finished model – perhaps because the mechanism is more complex than the way applications akin to ChatGPT generate images. Instead of passing hints to a picture generator (akin to DALL-E 3 for ChatGPT), Gemini generates images “natively” with no intermediate step.

Gemini Ultra is accessible as an API through Vertex AI, Google’s fully managed platform for AI developers, and AI Studio, Google’s online tool for application and platform developers. It also supports Gemini apps – but not totally free. Access to Gemini Ultra through what Google calls Gemini Advanced requires a subscription to the Google One AI premium plan, which is priced at $20 monthly.

The AI ​​Premium plan also connects Gemini to your broader Google Workspace account—think emails in Gmail, documents in Docs, presentations in Sheets, and Google Meet recordings. This is useful, for instance, when Gemini is summarizing emails or taking notes during a video call.

Gemini Pro

Google claims that Gemini Pro is an improvement over LaMDA by way of inference, planning and understanding capabilities.

Independent test by Carnegie Mellon and BerriAI researchers found that the initial version of Gemini Pro was actually higher than OpenAI’s GPT-3.5 at handling longer and more complex reasoning chains. However, the study also found that, like all major language models, this version of Gemini Pro particularly struggled with math problems involving several digits, and users found examples of faulty reasoning and obvious errors.

However, Google promised countermeasures – and the first one got here in the type of Gemini 1.5 Pro.

Designed as a drop-in substitute, Gemini 1.5 Pro has been improved in lots of areas compared to its predecessor, perhaps most notably in the amount of information it could actually process. Gemini 1.5 Pro can write ~700,000 words or ~30,000 lines of code – 35 times greater than Gemini 1.0 Pro. Moreover – the model is multimodal – it isn’t limited to text. Gemini 1.5 Pro can analyze up to 11 hours of audio or an hour of video in various languages, albeit at a slow pace (e.g., looking for a scene in an hour-long movie takes 30 seconds to a minute).

Gemini 1.5 Pro entered public preview on Vertex AI in April.

An additional endpoint, Gemini Pro Vision, can process text images – including photos and videos – and display text according to the GPT-4 model with Vision OpenAI.

Twins

Using Gemini Pro with Vertex AI. Image credits: Twins

Within Vertex AI, developers can tailor Gemini Pro to specific contexts and use cases through a tuning or “grounding” process. Gemini Pro can be connected to external third-party APIs to perform specific actions.

AI Studio includes workflows for creating structured chat prompts using Gemini Pro. Developers have access to each Gemini Pro and Gemini Pro Vision endpoints and might adjust model temperature to control creative scope and supply examples with tone and elegance instructions, in addition to fine-tune security settings.

Gemini Nano

The Gemini Nano is a much smaller version of the Gemini Pro and Ultra models, and is powerful enough to run directly on (some) phones, slightly than sending the job to a server somewhere. So far, it supports several features on the Pixel 8 Pro, Pixel 8, and Samsung Galaxy S24, including Summarize in Recorder and Smart Reply in Gboard.

The Recorder app, which allows users to record and transcribe audio with the touch of a button, provides a Gemini-powered summary of recorded conversations, interviews, presentations and more. Users receive these summaries even in the event that they do not have a signal or Wi-Fi connection available – and in a nod to privacy, no data leaves their phone.

Gemini Nano can be available on Gboard, Google’s keyboard app. There, it supports a feature called Smart Reply that helps you suggest the next thing you’ll want to say while chatting in the messaging app. The feature initially only works with WhatsApp, but can be available in additional apps over time, Google says.

In the Google News app on supported devices, the Nano enables Magic Compose, which allows you to compose messages in styles akin to “excited”, “formal”, and “lyrical”.

Is Gemini higher than OpenAI’s GPT-4?

Google has had this occur a number of times advertised Gemini’s benchmarking superiority, claiming that Gemini Ultra outperforms current state-of-the-art results on “30 of 32 commonly used academic benchmarks used in the research and development of large language models.” Meanwhile, the company claims that Gemini 1.5 Pro is best able to perform tasks akin to summarizing content, brainstorming, and writing higher than Gemini Ultra in some situations; it will probably change with the premiere of the next Ultra model.

However, leaving aside the query of whether the benchmarks actually indicate a greater model, the results that Google indicates appear to be only barely higher than the corresponding OpenAI models. And – as mentioned earlier – some initial impressions weren’t great, each amongst users and others scientists mentioning that the older version of Gemini Pro tends to misinterpret basic facts, has translation issues, and provides poor coding suggestions.

How much does Gemini cost?

Gemini 1.5 Pro is free to use in Gemini apps and, for now, in AI Studio and Vertex AI.

However, when Gemini 1.5 Pro leaves the preview in Vertex, the model will cost $0.0025 per character, while the output will cost $0.00005 per character. Vertex customers pay per 1,000 characters (roughly 140 to 250 words) and, for models like the Gemini Pro Vision, per image ($0.0025).

Let’s assume a 500-word article incorporates 2,000 characters. To summarize this text with the Gemini 1.5 Pro will cost $5. Meanwhile, generating an article of comparable length will cost $0.1.

Pricing for the Ultra has not yet been announced.

Where can you try Gemini?

Gemini Pro

The easiest place to use Gemini Pro is in the Gemini apps. Pro and Ultra respond to queries in multiple languages.

Gemini Pro and Ultra are also available in preview on Vertex AI via API. The API is currently free to use “within limits” and supports certain regions including Europe, in addition to features akin to chat and filtering.

Elsewhere, Gemini Pro and Ultra might be present in AI Studio. Using this service, developers can iterate on Gemini-based prompts and chatbots after which obtain API keys to use them of their applications or export the code to a more complete IDE.

Code Assistant (formerly AI duo for programmers), Google’s suite of AI-based code completion and generation tools uses Gemini models. Developers could make “large-scale” changes to code bases, akin to updating file dependencies and reviewing large snippets of code.

Google has introduced Gemini models in its development tools for the Chrome and Firebase mobile development platform and database creation and management tools. It has also introduced new security products based on Gemini technology, e.g Gemini in Threat Intelligence, a component of Google’s Mandiant cybersecurity platform that may analyze large chunks of probably malicious code and enable users to search in natural language for persistent threats or indicators of compromise.

This article was originally published on : techcrunch.com
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The company is currently developing washing machines for humans

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Forget about cold baths. Washing machines for people may soon be a brand new solution.

According to at least one Japanese the oldest newspapersOsaka-based shower head maker Science has developed a cockpit-shaped device that fills with water when a bather sits on a seat in the center and measures an individual’s heart rate and other biological data using sensors to make sure the temperature is good. “It also projects images onto the inside of the transparent cover to make the person feel refreshed,” the power says.

The device, dubbed “Mirai Ningen Sentakuki” (the human washing machine of the longer term), may never go on sale. Indeed, for now the company’s plans are limited to the Osaka trade fair in April, where as much as eight people will have the option to experience a 15-minute “wash and dry” every day after first booking.

Apparently a version for home use is within the works.

This article was originally published on : techcrunch.com
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Zepto raises another $350 million amid retail upheaval in India

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Zepto, snagging $1 billion in 90 days, projects 150% annual growth

Zepto has secured $350 million in latest financing, its third round of financing in six months, because the Indian high-speed trading startup strengthens its position against competitors ahead of a planned public offering next yr.

Indian family offices, high-net-worth individuals and asset manager Motilal Oswal invested in the round, maintaining Zepto’s $5 billion valuation. Motilal co-founder Raamdeo Agrawal, family offices Mankind Pharma, RP-Sanjiv Goenka, Cello, Haldiram’s, Sekhsaria and Kalyan, in addition to stars Amitabh Bachchan and Sachin Tendulkar are amongst those backing the brand new enterprise, which is India’s largest fully national primary round.

The funding push comes as Zepto rushes so as to add Indian investors to its capitalization table, with foreign ownership now exceeding two-thirds. TechCrunch first reported on the brand new round’s deliberations last month. The Mumbai-based startup has raised over $1.35 billion since June.

Fast commerce sales – delivering groceries and other items to customers’ doors in 10 minutes – will exceed $6 billion this yr in India. Morgan Stanley predicts that this market shall be value $42 billion by 2030, accounting for 18.4% of total e-commerce and a pair of.5% of retail sales. These strong growth prospects have forced established players including Flipkart, Myntra and Nykaa to cut back delivery times as they lose touch with specialized delivery apps.

While high-speed commerce has not taken off in many of the world, the model seems to work particularly well in India, where unorganized retail stores are ever-present.

High-speed trading platforms are creating “parallel trading for consumers seeking convenience” in India, Morgan Stanley wrote in a note this month.

Zepto and its rivals – Zomato-owned Blinkit, Swiggy-owned Instamart and Tata-owned BigBasket – currently operate on lower margins than traditional retail, and Morgan Stanley expects market leaders to realize contribution margins of 7-8% and adjusted EBITDA margins to greater than 5% by 2030. (Zepto currently spends about 35 million dollars monthly).

An investor presentation reviewed by TechCrunch shows that Zepto, which handles greater than 7 million total orders every day in greater than 17 cities, is heading in the right direction to realize annual sales of $2 billion. It anticipates 150% growth over the following 12 months, CEO Aadit Palicha told investors in August. The startup plans to go public in India next yr.

However, the rapid growth of high-speed trading has had a devastating impact on the mom-and-pop stores that dot hundreds of Indian cities, towns and villages.

According to the All India Federation of Consumer Products Distributors, about 200,000 local stores closed last yr, with 90,000 in major cities where high-speed trading is more prevalent.

The federation has warned that without regulatory intervention, more local shops shall be vulnerable to closure as fast trading platforms prioritize growth over sustainable practices.

Zepto said it has created job opportunities for tons of of hundreds of gig employees. “From day one, our vision has been to play a small role in nation building, create millions of jobs and offer better services to Indian consumers,” Palicha said in an announcement.

Regulatory challenges arise. Unless an e-commerce company is a majority shareholder of an Indian company or person, current regulations prevent it from operating on a listing model. Fast trading corporations don’t currently follow these rules.

This article was originally published on : techcrunch.com
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Wiz acquires Dazz for $450 million to expand cybersecurity platform

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Wizardone of the talked about names within the cybersecurity world, is making a major acquisition to expand its reach of cloud security products, especially amongst developers. This is buying Dazzlespecialist in solving security problems and risk management. Sources say the deal is valued at $450 million, which incorporates money and stock.

This is a leap within the startup’s latest round of funding. In July, we reported that Dazz had raised $50 million at a post-money valuation of just below $400 million.

Remediation and posture management – two areas of focus for Dazz – are key services within the cybersecurity market that Wiz hasn’t sorted in addition to it wanted.

“Dazz is a leader in this market, with the best talent and the best customers, which fits perfectly into the company culture,” Assaf Rappaport, CEO of Wiz, said in an interview.

Remediation, which refers to helping you understand and resolve vulnerabilities, shapes how an enterprise actually handles the various vulnerability alerts it could receive from the network. Posture management is a more preventive product: it allows a company to higher understand the scale, shape and performance of its network from a perspective, allowing it to construct higher security services around it.

Dazz will proceed to operate as a separate entity while it’s integrated into the larger Wiz stack. Wiz has made a reputation for itself as a “one-stop shop,” and Rappaport said the integrated offering will proceed to be a core a part of it.

He believes this contrasts with what number of other SaaS corporations are built. In the safety industry, there are, Rappaport said, “a lot of Frankenstein mashups where companies prioritize revenue over building a single technology stack that actually works as a platform.” It could be assumed that integration is much more necessary in cybersecurity than in other areas of enterprise IT.

Wiz and Dazz already had an in depth relationship before this deal. Merat Bahat — the CEO who co-founded Dazz with Tomer Schwartz and Yuval Ofir (CTO and VP of R&D, respectively) — worked closely with Assaf Rappaport at Microsoft, which acquired his previous startup Adallom.

After Rappaport left to found Wiz together with his former Adallom co-founders, CTO Ami Luttwak, VP of Product Yinon Costica and VP of R&D Roy Reznik, Bahat was one in all the primary investors. Similarly, when Bahat founded Dazz, Assaf was a small investor in it.

The connection goes deeper than work colleagues. Bahat and Rappaport are also close friends, and she or he was the second family of Mickey, Rappaport’s beloved dog, referred to as Chief Dog Officer Wiz (together with LinkedIn profile). Once the deal was done, the 2 faced two very sad events: each Bahat and Mika’s mother died.

“We hope for a new chapter of positivity,” Bahat said. The cycle of life does indeed proceed.

Rumors of this takeover began to appear earlier this month; Rappaport confirmed that they then began talking seriously.

But that is not the one M&A conversation Wiz has gotten involved in. Earlier this 12 months, Google tried to buy Wiz itself for $23 billion to construct a major cybersecurity business. Wiz walked away from the deal, which might have been the biggest in Google’s history, partly because Rappaport believed Wiz could turn into a fair larger company by itself terms. And that is what this agreement goals to do.

This acquisition is a test for Wiz, which earlier this 12 months filled its coffers with $1 billion solely for M&A purposes (it has raised almost $2 billion in total, and we hear the subsequent round will close in just a few weeks). . Other offers included purchasing Gem security for $350 million, but Dazz is its largest acquisition ever.

More mergers and acquisitions could also be coming. “We believe next year will be an acquisition year for us,” Rappaport said.

In an interview with TC, Luttwak said that one in all Wiz’s priorities now’s to create more tools for developers that have in mind what they need to do their jobs.

Enterprises have made significant investments in cloud services to speed up operations and make their IT more agile, but this shift has include a significantly modified security profile for these organizations: network and data architectures are more complex and attack surfaces are larger, creating opportunities for malicious hackers to find ways to to hack into these systems. Artificial intelligence makes all of this far more difficult when it comes to malicious attackers. (It’s also a chance: the brand new generation of tools for our defense relies on artificial intelligence.)

Wiz’s unique selling point is its all-in-one approach. Drawing data from AWS, Azure, Google Cloud and other cloud environments, Wiz scans applications, data and network processes for security risk aspects and provides its users with a series of detailed views to understand where these threats occur, offering over a dozen products covering the areas, corresponding to code security, container environment security, and provide chain security, in addition to quite a few partner integrations for those working with other vendors (or to enable features that Wiz doesn’t offer directly).

Indeed, Wiz offered some extent of repair to help prioritize and fix problems, but as Luttwak said, the Dazz product is solely higher.

“We now have a platform that actually provides a 360-degree view of risk across infrastructure and applications,” he said. “Dazz is a leader in attack surface management, the ability to collect vulnerability signals from the application layer across the entire stack and build the most incredible context that allows you to trace the situation back to engineers to help with remediation.”

For Dazz’s part, once I interviewed Bahat in July 2024, when Dazz raised $50 million at a $350 million valuation, she extolled the virtues of constructing strong solutions and this week said the third quarter was “amazing.”

“But market dynamics are what trigger these types of transactions,” she said. She confirmed that Dazz had also received takeover offers from other corporations. “If you think about the customers and joint customers that we have with Wiz, it makes sense for them to have it on one platform.”

And a few of Dazz’s competitors are still going it alone: ​​Cyera, like Dazz, an authority in attack surface management, just yesterday announced a rise of $300 million at a valuation of $5 billion (which confirms our information). But what’s going to he do with this money? Make acquisitions, after all.

Wiz says it currently has annual recurring revenue of $500 million (it has a goal of $1 billion ARR next 12 months) and has greater than 45% of its Fortune 100 customers. Dazz said ARR is within the tens of hundreds of thousands of dollars and currently growing 500% on a customer base of roughly 100 organizations.

This article was originally published on : techcrunch.com
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