Google has announced the phased rollout of its new ‘Gemini’ family of large language models with the Ultra version said to rival the abilities of OpenAI’s GPT-4.

What Is Gemini? 

Gemini, which Google describes as its “newest and most capable” large language model (LLM) and representing a “new era” for AI, is a highly advanced and multimodal AI model. Gemini is a foundational model and not a product like a chatbot. This means it’s designed to be integrated into Google’s existing (and future) products such as its Bard chatbot and Google Search.

The Key Difference 

The key difference to competing LLMs is Gemini’s native multimodality, which means it was built from the ground up to understand, process, combine, and generate different types of data seamlessly, i.e. text, code, audio, images, and video.

This approach differs from traditional multimodal models which often train separate components for different modalities and then stitch them together. As a result, Gemini can handle complex tasks involving various inputs more effectively than its predecessors, thereby making it particularly versatile and powerful.

Three Versions 

Google has produced three versions of the Gemini model, each one optimised for specific tasks. These are:

– Gemini Ultra. This is the largest and most capable version of the model, designed for highly complex tasks. For example, Google reports that it excels in various benchmarks, outperforming existing models and even human experts in Massive Multitask Language Understanding (MMLU). Gemini Ultra is particularly strong in fields requiring advanced reasoning and understanding, such as mathematics, physics, history, law, medicine, and ethics.

– Gemini Pro. This model version is versatile and has been optimised for scaling across a broad range of tasks. It has, therefore, now been integrated into Google Bard to enhance its capabilities. This upgrade has reportedly improved Bard’s performance in understanding and summarising information, reasoning, coding, and planning.

– Gemini Nano.  This version is the most efficient model, tailored for on-device tasks. Its efficiency makes it suitable for applications that require AI capabilities directly on mobile devices or other hardware with limited processing power.

Performance 

In terms of performance, Gemini is reported to have shown exceptional results, surpassing state-of-the-art models in many areas. Google claims, for example that Gemini can outperform OpenAI’s GPT-4 platform (which powers ChatGPT) on 30 of the 32 widely-used academic benchmarks!

Gemini has demonstrated advanced capabilities in not just understanding and reasoning across different modalities but also in coding, being able to understand, explain, and generate high-quality code in multiple programming languages.

Adding To Google’s Search? 

As expected, and intended, Google has been reported to be experimenting with integrating Gemini into its Search Generative Experience (SGE), where it has already shown improvements in speed and quality. This integration could have the potential for Gemini to enhance Google’s search capabilities significantly thereby upping the ante in the search engine market.

Downsides? 

Although Gemini’s exceptional abilities point to a “new standard” being set (as described by Gartner’s Chirag Dekate), this kind of power is bound to come with risk and downsides. For example:

– Possible ethical and societal Impacts. AI systems with advanced reasoning capabilities could still make decisions or produce outputs that reflect biases present in their training data, leading to potential ethical issues and unfair representations in sensitive areas.

– Privacy concerns. The extensive data processing capabilities of Gemini could raise significant privacy concerns, especially regarding personal data misuse, and these concerns could increase as this type of model become more integrated into everyday technologies, e.g. Gemini Nano on devices.

– Misinformation and manipulation. Something this powerful and multimodal could have the ability to seamlessly create realistic fake content could be exploited for crime, spreading misinformation, or manipulating public opinion.

– Dependence and skill erosion. A really powerful multimodal model like Gemini could lead to an overreliance on AI which could lead to a decline in human skills and critical thinking abilities.

– Security risks. Powerful AI models like Gemini could become targets for cyberattacks. If compromised, they could be used for malicious purposes, such as generating harmful content or disrupting critical digital infrastructure.

– Economic impacts. The effects of AI-driven automation on employment, job displacement in certain sectors, and inequality are only likely to be increased by Gemini. As already stated, the Ultra version is very strong in areas like mathematics, physics, history, law, and medicine.

– Regulatory and control challenges. The rapid advancement and complexity of AI models like Gemini make it difficult for regulatory frameworks to keep pace.

– Unpredictable outcomes. The increasing complexity of AI LLMs can lead to less transparent and predictable decision-making processes, therefore, making it difficult to understand and manage these systems effectively.

OpenAI Challenger

Sam Altman, OpenAI’s CEO, has indicated that as early as next year, it could be launching its own new ultra-powerful AI products that could compete with Gemini. Open AI also has the backing of Microsoft (which is currently the subject of a CMA antitrust investigation).

What Does This Mean For Your Business?

With the rollout of Google’s Gemini AI, businesses appear to be on the cusp of a new era in AI. Gemini, with its versions Ultra, Pro, and Nano, is not just another large language model, but it represents a leap forward in AI’s ability to understand, process, and generate a multitude of data types, including text, code, audio, images, and video. This multimodal functionality is a key differentiator, setting it apart from existing models in a value-adding way.

For businesses already leveraging Google’s suite of products, the integration of Gemini could mean a significant boost in efficiency and capability. The enhanced Bard chatbot and Google Search, powered by Gemini, are likely to deliver more accurate, nuanced, and comprehensive results. This could transform how businesses handle data, engage with customers, and develop content.

Also, the advanced capabilities of Gemini, especially in its Ultra version, offer unparalleled opportunities in areas requiring deep analysis and reasoning, like market research, product development, and strategic planning. Its ability to outperform other models and even human experts in certain tasks could provide businesses with insights and solutions that were previously unattainable.

However, this power comes with challenges and responsibilities. For example, its power and multimodal capabilities could be effectively exploited by bad actors and the advanced data processing capabilities of Gemini could pose privacy and security risks if not managed carefully. Additionally, as AI technology advances rapidly in this way, staying compliant with evolving regulatory frameworks is crucial and businesses must navigate these changes responsibly to avoid legal and reputational risks. Also, with the EU only just compiling its own provisional AI bill (which won’t become law for at least 2 years), and OpenAI set to introduce its own next generation LLM in 2024 it seems that effective regulation in the AI market looks like being incredibly challenging and likely to lag considerably behind the technology.

The increasing economic impacts of AI-driven automation, particularly in employment, also warrant attention and businesses may be left with decisions such as how to reskill and redeploy their workforce to mitigate the effects of ultra-powerful LLMs and their AI chatbots eating into wider areas of human expertise.

Google’s Gemini, therefore, presents businesses with a wealth of opportunities for growth and innovation and yet, it also underscores the importance of a balanced approach in leveraging AI technology, and the need for regulation to keep up. As the AI landscape continues to evolve, businesses must remain adaptable, ethical, and vigilant to harness the full potential of AI while mitigating its risks. Gemini looks like being a disruptive competitive advantage for Google in the short term. The future competition in the AI market, with companies like OpenAI gearing up to introduce their own advanced models, indicates an exciting and challenging road ahead for businesses navigating the world of AI.

A single 1976 $4.01 cheque from (and signed by) Apple co-founder Steve Jobs has been sold at auction for a whopping $46,063.

The cheque, written just four months after Apple was founded, was written for a purchase at Radio Shack, where co-founder Steve Wozniak famously bought a TRS-80 Micro Computer System.

The components from the computer were used by Wozniak to help build the ‘blue box’ which could enable users to make free long-distance phone calls. Beginning in 1972 the pair reportedly sold around 200 of the blue boxes for $150 each and this was the first commercial collaboration between Jobs and Wozniak.

Steve Jobs is quoted as saying: “If it hadn’t been for the Blue Boxes, there would have been no Apple. I’m 100% sure of that.” 

Toyota Financial Services (TFS), a subsidiary of Toyota Motor Corporation, has warned customers that it recently suffered a data breach which exposed sensitive personal and financial data.
The correspondence with affected customers follows Toyota confirming last month that unauthorised access on some of its Europe (and Africa) systems had been detected. Medusa ransomware reported that it was behind Toyota’s system being compromised and issued Toyota with an $8,000,000 ransom request to have the stolen data deleted.
The advice from TFS to its customers is to contact their bank to take additional security precautions, add 2FA to their online accounts, monitor any unusual activities, and obtain a current credit report from Schufa (a German credit rating agency). Toyota has also said that it has informed the responsible state data protection officer (for North Rhine-Westphalia) in compliance with GDPR.

Berlin-based green search engine company Ecosia has released a chatbot with a “green answers” option and ploughs all its advertising profits into tree-planting.

Ecosia AI Chat  

The not-for-profit company, which has been developing its “green search” since 2019 to help users make climate-active decisions about what/who they click on has announced the introduction of its Ecosia AI Chat feature. Ecosia says the “green filter” AI chatbot, currently in beta and available in select countries, means “technology could be harnessed for good.” Ecosia Chat, which is powered by a large language model AI (from OpenAI), is a chatbot designed to help users be more climate-active daily and gives sustainability-focused responses.

Uses The Green Persona 

The new chatbot, incorporated into its search offers users a “green answers” option which triggers a layered green persona that can provide users with more sustainable results and answers. For example, Ecosia says “You can ask it to plan a climate action weekend or write a Shakespeare sonnet about trees – the possibilities are virtually unlimited.” 

Independent 

Ecosia is one of the first independent search engines to roll out its own generative AI chatbot and is keen to emphasise the chatbot’s low carbon footprint, and how this aligns with the company’s environmental commitment.

Tree-Planting 

One of the key elements of Ecosia’s environmental focus is using all the profits from the advertising on its search engine to fund tree-planting around the world, which it gives regular updates about on its website. For example, this month, its update features news from its tree-planting partner Symagine Solutions in West Bengal, South-East India that more than one million trees from 23 species have been planted by Ecosia community over the past two years.

In addition to tree-planting, Ecosia also says that it puts profits into producing enough solar energy to power all its searches twice over.

Other Green Features 

Other green features that Ecosia includes in its search engine results to enable users to make more conscious decisions include:

– Placing a green leaf icon alongside the websites of planet-friendly organisations.

– Placing a fossil fuel icon next to “some of the most destructive actors” such as banks who are financing fossil fuels.

COP28 In Dubai 

The announcement of Ecosia’s latest green search features came just before the beginning of COP28 in Dubai, the latest Climate Change Conference, which Ecosia has criticised saying “we got together with climate activists to hold COP28 accountable.” 

Hallucinations 

Despite Ecosia AI Chat’s green features, like many other new AI chatbots, it’s been reported that it suffers sometimes giving out incorrect information, i.e. AI hallucinations.

What Does This Mean For Your Organisation? 

Considering that the UN recently reported that the world was on track for a 3°C rise in temperatures within this century, despite the COP21 (2015) Paris Agreement establishing measures to keep the global rise in temperatures well below 2°C, it’s not surprising that Ecosia’s been critical of COP28 being held in Dubai. For example, as Ecosia points out, COP28’s president, Sultan Al Jaber, is the CEO of the Abu Dhabi National Oil Company ADNOC.  That aside, Ecosia is non-profit, putting its money where its mouth is with a green-matters-first approach (putting profits into tree planting), and with Ecosia being powered by solar energy (in addition to its green search filtering) it has some clear differentiating factors in the AI chatbot market that may be valued by many users. The fact that it’s one of the rare independents (not openly linked to the big players) may also help its credentials and traction.

Clearly, Ecosia’s boss, Christian Kroll, believes that AI has opened up the market more for smaller independents and believes his very different offering will enable him (and perhaps others) to target a global increase within search engine market share that they wouldn’t have been able to before AI chatbots came along. The choice offered to users by rule-changes brought about by the EU Digital Markets Act from March 2024 may also favour companies like Ecosia as consumers will be able to choose which browsers, search engines, and virtual assistants they install, perhaps to align with their environmental concerns.

That said, Ecosia faces some tough competition from more established generative AI chatbots and new ones which are being introduced thick and fast. Also, Ecosia would probably admit that being powered by an OpenAI LLM means that it doesn’t have full control over just how ‘green’ its chatbot is, and that it doesn’t have the answer to solving the bigger issue of how much energy and water generative AI chatbots use. Specifically, they create huge energy and cooling demands at the data-centre level. Also, it could be argued that planting trees (although beneficial) is not stopping all the carbon from being produced in the first place (a criticism of offsetting). However, Ecosia’s very different green offering is likely to be attractive to many people going forward and could put the organisation in a good position to take advantage of law changes that could favour it next year.

If you’d like to save time and conveniently view various types of files like PDFs, images, and text documents directly in the browser, eliminating the need for multiple separate applications, here’s how to use Google Chrome as simple, all-purpose, drag and drop file viewer:

– Open a new tab in Chrome.

– Drag and drop a document or image file into the tab.

– Chrome will display the file, allowing you to view PDFs, images, text files, and even some video and audio files without needing a separate application.

Following on from the launch of OpenAI’s ChatGPT, Google’s Bard (and Duet), Microsoft’s Copilot, and X’s Grok, now Amazon has announced that it will soon be launching its own ‘Q’ generative AI chatbot (for business).

Cue Q 

Amazon has become the latest of the tech giants to announce the introduction of its own generative AI chatbot. Recently announced at the Las Vegas conference for its AWS, ‘Q’ is Amazon’s chatbot that will be available as part of its market-leading AWS cloud platform. As such, Q is being positioned from the beginning as very much a business-focused chatbot with Amazon introducing the current preview version as: “Your generative AI–powered assistant designed for work that can be tailored to your business.” 

What Can It Do? 

The key point from Amazon is that Q is a chatbot that can be tailored to help your business get the most from AWS. Rather like Copilot is embedded in (and works across) Microsoft’s popular 365 apps, Amazon is pitching Q as working across many of its services, providing better navigation and leveraging for AWS customers with many (often overlapping) service options. For example, Amazon says Q will be available wherever you work with AWS (and is an “expert” on patterns in AWS), in Amazon QuickSight (its business intelligence (BI) service built for the cloud), in Amazon Connect (as a customer service chatbot helper), and will also be available in AWS Supply Chain (to help with inventory management).

Just like other AI chatbots, it’s powered by AI models which in this case includes Amazon’s Titan large language model. Also, like other AI chatbots, Q uses a web-based interface to answer questions (streamlining searches), can provide summaries, generate content and more. However, since it’s part of AWS, Amazon’s keen to show that it adds value by doing so within the context of the business it’s tailored to and becomes an ‘expert’ on your business. For example, Amazon says: “Amazon Q can be tailored to your business by connecting it to company data, information, and systems, made simple with more than 40 built-in connectors. Business users—like marketers, project and program managers, and sales representatives, among others—can have tailored conversations, solve problems, generate content, take actions, and more.” The 40 connectors it’s referring to include popular enterprise apps (and storage depositories) like S3, Salesforce, Google Drive, Microsoft 365, ServiceNow, Gmail, Slack, Atlassian, and Zendesk. The power, value, and convenience that Q may provide to businesses may also, therefore, help with AWS customer retention and barriers to exit.

Benefits 

Just some of the many benefits that Amazon describes Q as having include:

– Delivering fast, accurate, and relevant (and secure) answers to your business questions.

– Quickly connecting to your business data, information, and systems, thereby enabling employees to have tailored conversations, solve problems, generate content, and take actions relevant to your business.

– Generating answers and insights according to the material and knowledge that you provide (backed up with references and source citations).

– Respecting access control based on user permissions.

– Enabling admins to easily apply guardrails to customise and control responses.

– Providing administrative controls, e.g. it can block entire topics and filter both questions so that it responds in a way that is consistent with a company’s guidelines.

– Extracting key insights on your business and generating reports and summaries.

– Easy deployment and security, i.e. it supports access control for your data and can be integrated with your external SAML 2.0–supported identity provider (Okta, Azure AD, and Ping Identity) to manage user authentication and authorisation.

When, How, And How Much? 

Q’s in preview at the moment with Amazon giving no exact date for its full launch. Although many of the Q capabilities are available without charge during the preview period, Amazon says It will be available in two pricing plans: Business and Builder. Amazon Q Business (its basic version) will be priced at $20/mo, per-user, and Builder at $25/mo, per-user. The difference appears to be that Builder provides the real AWS expertise plus other features including debugging, testing, and optimising your code, troubleshooting applications and more. Pricewise, Q is cheaper per month/per user than Microsoft’s Copilot and Google’s Duet (both $30).

Not All Good 

Despite Amazon’s leading position in the cloud computing world with AWS, and its technological advances in robotics (robots for its warehouses), its forays in space travel (with Amazon Blue) and into delivery-drone technology, it appears that it may be temporarily lagging in AI-related matters. For example, in addition to being later to market with this AI chatbot ‘Q’, in October, a Stanford University index ranked Amazon’s Tital AI model (which is used in Q) as bottom for transparency in a ranking of the top foundational AI models with only 12 per cent (compared to the top ranking Llama 2 from Meta at 54 per cent). As Stanford puts it: “Less transparency makes it harder for other businesses to know if they can safely build applications that rely on commercial foundation models; for academics to rely on commercial foundation models for research; for policymakers to design meaningful policies to rein in this powerful technology; and for consumers to understand model limitations or seek redress for harms caused.” 

Also, perhaps unsurprisingly due to Q only just being in preview, some other reports about it haven’t been that great. For example, feedback about Q (leaked from Amazon’s internal channels and ticketing systems) highlight issues like severe hallucinations and leaking confidential data. Hallucinations are certainly not unique to Q as reports about and admissions by OpenAI about ChatGPT’s hallucinations have been widely reported.

Catching Up 

Amazon also looks like it will be makingeven greater efforts to catch up in the AI development world. For example, in September it said Alexa will be getting ChatGPT-like voice capabilities, and it’s been reported that Amazon’s in the process of building a language model called Olympus that could be bigger and better than OpenAI’s GPT-4!

What Does This Mean For Your Business?

Although a little later to the party with AI chatbot, Amazon’s dominance in the cloud market with AWS means it has a huge number of business customers to sell its business-focused Q to. This will not only provide another revenue stream to boost its vast coffers but will also enhance, add value to, and allow customers to get greater leverage from the different branches of its different cloud-related services. What with Microsoft, Google, X, Meta, and others all having their own chatbot assistants, it’s almost expected that any other big players in the tech world like Amazon would bring out their own soon.

Despite some (embarrassing internal) reviews of issues in its current preview stage and a low transparency ranking in a recent Stanford report, Amazon clearly has ambitions to make fast progress in catching up in the AI market. With its market power, wealth, and expertise in diversification and its advances in technologies like space travel and robotics and the synergies it brings (e.g. satellite broadband), you’d likely not wish to bet against Amazon making quick progress to the top in AI too.

Q therefore is less of a standalone chatbot like ChatGPT (OpenAI and former workers have helped develop AI for others) and more of Copilot and Duet arrangement in that it’s being introduced to enhance and add value to existing Amazon cloud services, but in a very focused way (more so for Builder) in that it’s “trained on over 17 years’ worth of AWS knowledge and experience”.

Despite Q still being in preview, Amazon’s ambitions to make a quantum leap ahead are already clear if the reports about its super powerful, GPT-4 rivalling (still under development) Olympus model are accurate. It remains to be seen, therefore, how well Q performs once it’s really out there and its introduction marks another major move by a serious contender in the rapidly evolving and growing generative AI market.