Connect with us

Technology

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

Published

on

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
Continue Reading
Advertisement
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

Technology

Coatue raises $1 billion for AI betting

Published

on

By

Philippe Laffont

Coatue Management, a hedge fund that has invested heavily in tech startups throughout the pandemic boom, is raising $1 billion to support artificial intelligence corporations, Bloomberg reported on Monday.

The funds that can contribute to the corporate’s flagship fund will probably be obtained primarily from institutional investors. However, the report shows that wealthy individuals with accounts at brokerage Raymond James and Associates can even spend money on Coatue.

Coatue, which manages nearly $50 billion in assets, invested in greater than 170 VC-backed corporations in 2021, based on PitchBook data. Since then, Coatue has dramatically slowed its pace of investing in startups, supporting only 81 corporations in 2022 and around 30 corporations in 2023.

However, the cross-border investor shouldn’t be done investing in private corporations. According to PitchBook data, in 2024 Coatue supported 29 startups. The company’s latest AI-focused investments include Glean, Scale AI and Skild AI, which is constructing a general-purpose AI robot. Philippe Laffont, founding father of Coatue (pictured above), said they’re particularly enthusiastic about humanoid robots with artificial intelligence-powered brains.

This article was originally published on : techcrunch.com
Continue Reading

Technology

Mom and son Game Changer Academy founders help black gamers get 150,000. dollars in NIL transactions

Published

on

By

gamers, NIL, Black


Kendall Hamilton and his mother, Dr. Gigi, help Black gamers land lucrative name, image, likeness (NIL) deals and influence the industry through their organization Game Changer Academy.

In highschool, Hamilton rose to prominence as a player himself. Although his mother was initially concerned about his profession path, her support for Hamilton led to his promotion in Rocket League. Hamilton and his mother were among the many top ten players in the virtual game showing others Black families the right way to succeed in esports.

At Game Changer Academy, Hamilton is a performance improvement coach and mental health advocate. Thanks to his own success, he knows concerning the great opportunities the sport offers, akin to scholarships and NIL offers. Now he and his mother were working to make those offers available to other black players like him. So far, the mother and son duo have acquired over 150,000 for his or her clients. dollars.

As for Dr. Gigi, she uses her background in workforce development to help families turn passions into fruitful opportunities. She helped families learn the way gaming could lead on to scholarships and future offers. The licensed psychotherapist also wants to scale back the gap between black gamers and industrial success.

Their efforts are contributing to a greater emphasis on diverse players – 15% of them discover as black, in accordance with New Zoo. Understanding the potential financial gains from the booming industry, the duo stays committed to reaching Black youth captivated with esports to speed up their careers.

Their newest enterprise, Game On: Virtual Experience – Gaming, Mental Health, and Personal Development, hopes to proceed this mission. The event, which can happen on November 4, will connect players and inform them concerning the opportunity to shape their future in this industry. Additionally, there shall be speak about protecting your mental health while pursuing your passions while constructing an empire.

Game Changer Academy is diversifying the esports industry and preparing Black gamers to take the sector. Registration for the event is now open to all families with ready-to-play players.


This article was originally published on : www.blackenterprise.com
Continue Reading

Technology

Columbus says ransomware gang stole personal information of 500,000 Ohioans

Published

on

By

The city of Columbus, the capital of Ohio, confirmed that hackers stole the personal information of 500,000 residents during a July ransomware attack.

In filing In an interview with Maine’s attorney general, Columbus confirmed that a “foreign threat actor” breached its network to access information including residents’ names, dates of birth, addresses, identification documents, social security numbers and checking account information .

Ohio’s most populous city, with about 900,000 people, said about half 1,000,000 people were affected, even though it didn’t confirm the precise number of victims.

The regulatory filing comes after Columbus was the goal of a ransomware attack on July 18 this 12 months by city officials he claimed “thwart” it by disconnecting your network from the Internet.

Rhysida, the ransomware gang accountable for last 12 months’s cyber attack on the British Library, claimed responsibility for the August attack on Columbus. At the time, the gang said it had stolen 6.5 terabytes of data from the Ohio city, including “databases, internal employee logins and passwords, a full server dump of city emergency services applications, and … access from city video cameras,” in response to local news reports.

Rhysida demanded 30 bitcoins, or roughly $1.9 million on the time of the cyberattack, as payment for the stolen data.

Two weeks after the cyberattack, Columbus Mayor Andrew Ginther told the general public that the stolen data was likely “corrupted” and “unusable.”

The accuracy of Ginther’s statement was called into query the day after David Leroy Ross, a cybersecurity researcher also often called Connor Goodwolf, revealed that the personal information of a whole lot of 1000’s of Columbus residents had been placed on the dark web.

In September, Columbus sued Ross, alleging that it “threatened to make stolen city data available to third parties who otherwise would not have readily available means to obtain stolen city data.” A judge issued a brief restraining order against Ross, stopping him from accessing the stolen data.

In a listing published Monday by TechCrunch on the leak site, Rhysida claims to have transferred 3.1 terabytes of “unsold” data stolen from Columbus, amounting to greater than 250,000 files.

This article was originally published on : techcrunch.com
Continue Reading
Advertisement

OUR NEWSLETTER

Subscribe Us To Receive Our Latest News Directly In Your Inbox!

We don’t spam! Read our privacy policy for more info.

Trending