Artificial intelligence is rapidly changing many aspects of how we work and live. (How many stories did you read last week about self-driving cars and job-stealing robots? Perhaps your holiday shopping involved some AI algorithms, as well.) But despite the constant flow of news, many misconceptions about AI remain.
AI doesn’t think in our sense of the word at all, Scriffignano explains. “In many ways, it’s not really intelligence. It’s regressive.”
IT leaders should make deliberate choices about what AI can and can’t do on its own. “You have to pay attention to giving AI autonomy intentionally and not by accident,”
6,742 Comments
Tomi Engdahl says:
Eliot Brown / Wall Street Journal:
Masayoshi Son’s $100B AI investment pledge to Trump would require a massive fundraising effort, new debt, or selling some of SoftBank’s holdings to raise cash
What’s Behind Masayoshi Son’s $100 Billion Pledge to Donald Trump
Following through will require some combination of a massive fundraising effort, new debt or selling chunks of his company’s holdings to raise cash
https://www.wsj.com/finance/softbank-ceo-trump-deal-ca0d3ab3?st=dWEURZ&reflink=desktopwebshare_permalink
Tomi Engdahl says:
Todd Spangler / Variety:
CAA partners with YouTube to help CAA clients identify and remove AI-generated content that features their likeness, with a wider rollout planned in early 2025 — In what’s being touted as the first partnership of its kind, CAA is collaborating with YouTube on a program promising to let actors …
YouTube Teams With CAA to Let Talent Identify — and Pull Down — AI Deepfakes of Themselves
https://variety.com/2024/digital/news/caa-youtube-talent-ai-deepfakes-remove-1236251470/
In what’s being touted as the first partnership of its kind, CAA is collaborating with YouTube on a program promising to let actors, athletes and other talent fight back against AI-generated fakes uploaded to the video platform.
YouTube’s message to Hollywood is that it’s trying to be a good partner to creative industries by taking “proactive steps to build responsible AI.” Under the partnership, CAA clients, “many of whom have been impacted by recent AI innovations,” will have access to YouTube’s early-stage likeness management technology, which is designed to identify and manage AI-generated content featuring faces on YouTube “at scale,” according to the companies.
Tomi Engdahl says:
Myles McCormick / Financial Times:
The NERC, overseen by the FERC, warns soaring US electricity demand from data centers to power AI could strain US and Canadian grids, risking blackouts — Surging demand from tech sector could overwhelm generation capacity, report says — North America’s electricity grid faces …
https://www.ft.com/content/7c241e6f-e9c1-4f45-883a-8d46e6bf8cd8
Tomi Engdahl says:
Jordan Novet / CNBC:
Salesforce says it will hire 2,000 people to sell AI agent software, a month after saying it would hire 1,000 for the task and two years after laying off 7,000+ — Salesforce will hire 2,000 people to sell artificial intelligence software to clients, CEO Marc Benioff said on Tuesday …
Salesforce will hire 2,000 people to sell AI products, CEO Marc Benioff says
https://www.cnbc.com/2024/12/17/salesforce-will-hire-2000-people-to-sell-ai-products-benioff-says.html
Salesforce will bring on 2,000 more salespeople specializing in artificial intelligence, CEO Marc Benioff said at an event in San Francisco on Tuesday.
The second generation of Salesforce’s AI agent software will become available to customers in February 2025.
The cloud software company, which targets sales reps, marketers and customer service agents, is among the many technology companies hoping to boost revenue with generative AI features.
“We’re adding another couple of thousand salespeople to help sell these products,” Benioff said at a company event in San Francisco. “We already had 9,000 referrals for the 2,000 positions that we’ve opened up. It’s amazing.”
On Tuesday, Salesforce said the second generation of its Agentforce technology creating and operating AI agents will become available to customers in February 2025. Agentforce will be able to tackle sophisticated questions in Salesforce’s Slack communications app, based on all available data.
Salesforce is ramping up its AI sales team almost two years after announcing it was laying off more than 7,000 employees to better reflect economic conditions. As of Jan. 31, 2024, headcount stood at 72,682, down about 1% from two years earlier, according to filings.
Benioff said Salesforce’s homepage now features an experimental AI agent that can respond to user queries about the company’s products. Salesforce customers in need of assistance can visit a chat-based help page that conducts 32,000 conversations a week. About 5,000 are getting escalated to humans as a result of current AI capabilities, down from 10,000 before, Benioff said.
Microsoft
has been selling a series of Copilot-branded AI tools. But if you check Microsoft’s website to see how it is automating customer support, Benioff said, “you can’t find it.”
The websites for Copilot and Microsoft’s Azure cloud do have agents, though.
“It’s so interesting Benioff said that, given Microsoft runs one of the world’s largest customer support teams — and we’ve been customer zero for Copilot from the very start,” Microsoft’s chief marketing officer for AI at work, Jared Spataro, said in a statement. “In customer service, Copilot is helping resolve cases 11.5% faster. Our sales teams are seeing real impact too, driving 9.4% higher revenue per seller and freeing up time to focus on strategic, value-driven work.”
Tomi Engdahl says:
Marina Temkin / TechCrunch:
As the AI industry booms, non-AI startups that raised a Series A 18 months ago are likely facing challenges in raising a Series B, even with good revenue growth — Earlier this year, IVP general partner Tom Loverro, proclaimed that the post-pandemic downturn is over, and companies …
AI boom masks fundraising struggles for non-AI startups
https://techcrunch.com/2024/12/17/ai-boom-masks-fundraising-struggles-for-non-ai-startups/
Tomi Engdahl says:
Executive Insights: The Era of Contact Center AI Copilots — How AI copilots are transforming customer experience and agent performance.
The Era of Contact Center AI Copilots
https://www.genesys.com/blog/post/the-era-of-contact-center-ai-copilots?utm_source=techmeme&utm_medium=syndication&utm_campaign=january2025-techmeme
ChatGPT from OpenAI continues to have an impact in all industries, as artificial intelligence (AI) makes a leap in capabilities that render it more human-like. These popular technologies have created widespread awareness of the power of large language models (LLMs) and generative AI — and what they can do for contact centers and customer experience, in particular.
Any transformative technology comes with early pitfalls and, in the case of LLMs and generative AI, hallucinations, data rights and privacy are causing businesses to proceed with caution. These have contributed to concerns that the technology isn’t ready for widespread, autonomous business use.
Capabilities keep improving as bots evolve to virtual agents using LLMs and generative AI to handle more tasks with 24/7 coverage and to free up and scale your contact center workforce for more complex workloads. However, more time and technology guardrails are needed for pure, autonomous virtual agent trust and success.
But now AI copilots have arrived and they’re making a leap forward in many human-assisted use cases.
The Advantages of Agent Copilots
Agent copilots offer a great opportunity to take all the functionality of LLMs and use that to help human agents do their jobs more consistently, effectively and efficiently.
Contact center copilots leverage generative AI to provide dynamic, precise and personalized support, moving beyond rigid, scripted responses. This flexibility enables copilots to help agents handle complex tasks, continuously improve through ongoing learning, and deliver increasingly accurate and relevant solutions.
Their ability to integrate across multiple platforms and applications further enhances their utility. And that makes them versatile and effective for contact center agents.
Because agent copilots are integrated with advanced AI functionality, they offer real-time, context-aware assistance. This enhances agent productivity by proactively predicting and seamlessly integrating with user workflows.
Agent copilots provide proactive knowledge and actions and use context to personalize responses based on individual preferences. Not only do they save time, but they allow agents to offer more consistent service to customers.
Copilots require a human in the loop to review and approve their work, significantly reducing the risk of providing incorrect information. You can also use a compliance bot to monitor and ensure accuracy.
For example, when a customer calls with a question about how to do something with a product, even a new agent with limited expertise can assist effectively with a copilot. The agent copilot accurately understands the customer’s intent and has access to the latest information from the full knowledge base.
Here are some ways agent copilots and humans work together to benefit the contact center.
Streamline after-call work
When an agent takes a customer call, they are expected to take notes throughout the conversation, capturing the nature of the inquiry and outlining the next steps.
After the call, agents typically engage in after-call work, initiating the promised processes and following up according to a workflow that can take several minutes. This process often relies on the agent’s memory of details and their individual interpretation.
Agent copilots streamline these tasks by automatically summarizing the call, allowing agents to focus on the conversation rather than taking notes. It understands the workflows and customer intents, incorporating them into the summary and initiating the appropriate actions. For example, it might recommend, “When opening this case, follow steps X, Y, and Z.” More critically, the copilot can integrate directly into the workflow, passing on key intents from the conversation and advising the agent on any remaining details needed to complete the process — all while the customer is still on the line.
More consistent and accurate wrap-up codes
Wrap-up codes applied at the end of an interaction categorize the nature and outcome of the call. They help business administrators analyze call patterns, assess agent performance and identify common customer issues. These codes also offer insights into frequent reasons for contact, the effectiveness of call resolutions and areas that need improvement. Agents are responsible for selecting these codes manually.
Business administrators often want to use a wide range of wrap-up codes — ideally categorizing callers into hundreds of segments. However, asking an agent to sift through hundreds of options at the end of a call is impractical, leading to the most popular codes being selected more frequently.
With an agent copilot, wrap codes can be automatically selected based on the copilot’s understanding of the interaction. This allows administrators to use as many codes as they need. The copilot generates a short list of the most relevant codes, or even a single code, which the agent can either accept or adjust as needed.
In addition to saving agents’ time, there’s huge benefit from more accurate reporting, consistency and lack of bias.
Recommend next-best actions
Genesys Cloud™ Agent Copilot uses advanced AI capabilities to optimize the next-best action by accurately interpreting user intent and presenting the most appropriate action to the agent. Administrators can define intents either by using a natural language understanding (NLU) model or by describing the intents manually. A large language model will then map these inputs to the corresponding intents.
Once the intent is identified, administrators can configure it to trigger a variety of actions, such as executing a specific action based on the data, launching a script or form, accessing a knowledge article or integrating with a third-party application accessible from the agent desktop.
One key advantage of the Genesys engine is its ability to extract entities, allowing us to pre-populate the next best action with relevant data. Whether it’s customer details or product information, this enriched data enhances the precision and effectiveness of the next best offer generated by the AI-driven systems.
Training Considerations for Agent Copilots
Agent copilots are trained on comprehensive business data, reducing the need for traditional, extensive training for human agents. Rather than requiring agents to memorize large amounts of information, the copilots act as “knowledge managers.” They offer real-time guidance and support.
This allows agents to learn and access information as needed. Additionally, it streamlines the learning process and improves efficiency.
Agent copilots are also trained on an organization’s unique customer data, rather than general internet data. They use real conversations between the company and its customers.
As agents provide information on products, processes or customer concerns, the copilot leverages transcriptions of these interactions to continually refine and enhance its models, ensuring it delivers relevant and accurate support.
This approach minimizes hallucinations by relying on verified, reliable data instead of questionable internet sources. With hundreds or thousands of customer interactions happening daily, the copilot continually updates and refines its insights, ensuring that agents access increasingly precise and accurate information.
Lastly, agent copilots can be trained using an organization’s unique knowledge bases, which typically contain comprehensive public and private information about the business and its products, including how they function. Imagine transforming all this information within a knowledge base into a contact center copilot that augments agent support, offering instant access to detailed and accurate knowledge.
Tomi Engdahl says:
Google DeepMind:
Google introduces FACTS Grounding benchmark for evaluating the factuality of LLMs, and announces a leaderboard that ranks Gemini 2.0 Flash Experimental on top — Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses …
FACTS Grounding: A new benchmark for evaluating the factuality of large language models
https://deepmind.google/discover/blog/facts-grounding-a-new-benchmark-for-evaluating-the-factuality-of-large-language-models/
Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations
Large language models (LLMs) are transforming how we access information, yet their grip on factual accuracy remains imperfect. They can “hallucinate” false information, particularly when given complex inputs. In turn, this can erode trust in LLMs and limit their applications in the real world.
Today, we’re introducing FACTS Grounding, a comprehensive benchmark for evaluating the ability of LLMs to generate responses that are not only factually accurate with respect to given inputs, but also sufficiently detailed to provide satisfactory answers to user queries.
We hope our benchmark will spur industry-wide progress on factuality and grounding. To track progress, we’re also launching the FACTS leaderboard on Kaggle. We’ve already tested leading LLMs using FACTS Grounding and have populated the initial leaderboard with their grounding scores. We will maintain and update the leaderboard as the field advances.
Tomi Engdahl says:
New York Times:
Sources: OpenAI is working to sever the nonprofit’s control while compensating its board, possibly in the billions, and promised investors a two-year schedule
https://www.nytimes.com/2024/12/17/technology/openai-nonprofit-control.html
Tomi Engdahl says:
Anna Tong / Reuters:
NYC-based AI-powered accounting startup Basis raised a $34M Series A led by Khosla Ventures, with Nat Friedman, Jeff Dean, Adam D’Angelo, and others investing
AI startup Basis raises $34 million for accounting automation ‘agent’
https://www.reuters.com/technology/artificial-intelligence/ai-startup-basis-raises-34-million-accounting-automation-agent-2024-12-17/
New York-based Basis is part of a category of AI startups creating autonomous agents, or systems that use AI to perform actions on their own. Executives in the field such as OpenAI CFO Sarah Friar have said such systems will dominate the AI agenda next year, as models have recently gotten to the point where they can carry out long-term planning.
Basis’ product, which they specifically sell to accounting firms, is capable of performing various workflows such as entering transactions and double-checking data accuracy, and integrates with popular ledger systems like Intuit’s (INTU.O)
, opens new tab QuickBooks and Xero (XRO.AX), opens new tab, the company said.
Tomi Engdahl says:
Konenäkö helpottaa kuljetusrobottien toimintaa
https://www.uusiteknologia.fi/2024/12/18/konenako-helpottaa-kuljetusrobottien-toimintaa/
Kuljetusrobottien talvikausi on alkamassa, joten Suomessa kehitettyä talviosaamista tarvitaan jälleen. Akkukäyttöisiä robotteja Starship Technologies kehittää Viron lisäksi Suomessa. Pääkonttori on Yhdysvalloissa sekä myyntitoimistot Britanniassa ja Saksassa.
Suomessa Starshipin kuljetusrobottien toiminta käynnistyi huhtikuussa 2022 Espoon Otaniemessä. Laajemminkin Suomi on yritykselle tärkeä. Iso osa robottiteknologian ja kuljetuspalvelun tuotekehityksestämme on tehty Suomessa.’’Robottiemme menestys Suomessa on osoitus siitä, että kehittyneenä korkean teknologian maana Suomi on nopea ottamaan käyttöön kestävää kehitystä edistävää teknologiaa”, sanoo Starship Technologiesin Heinla.
Starshipin kuljetusrobotissa on kaikkiaan 12 kameraa, useita antureita ja tutkapiirejä. Robotti hyödyntää liikkuessaan uusinta tietokonenäköä ja GPS-paikannusta. Siinä on myös ääniominaisuus, jonka avulla voi kommunikoida läheisyydessä olevien kanssa.
Robotti osaa talviominaisuuksien avulla myös havaita lumikasoja, joka perustuu tietokonenäön ja esteiden havaitsemisen teknologioiden yhdistelmään. Myös parempi reitin suunnittelu ja terävämmät käännökset lumikasojen välttämiseksi. Myös hälytysominaisuudet , joiden avulla pystytään havaitsemaan paremmin robotin lumeen juuttumisen, ja uusia liiketekniikoita lumesta irrottautumiseen.
Maailmalla yrityksen robotit ovat kulkeneet jo 15 miljoonaa kilometriä ja suorittaneet yli seitsemän miljoonaa autonomista toimitusta ympäri maailmaa. Päivittäin ne tekevät jopa 150 000 tienylitystä päivittäin
Tomi Engdahl says:
Getting started with ML/AI in Imagimob AI and IAR Embedded Workbench for Arm
This video gives an overview on how a machine learning application can be created from a starter project in Imagimob AI to a final embedded application in IAR Embedded Workbench for Arm.
Imagimob AI integrates with the IAR Embedded Workbench and allows you to add Tensorflow models to your projects and convert them to C source code.
https://www.iar.com/knowledge/learn/programming/getting-started-with-mlai-in-imagimob-ai-and-iar-embedded-workbench-for-arm/
Tomi Engdahl says:
IAR Systems enables powerful AI/ML applications based on Alif Semiconductor’s microcontrollers and fusion processors
The partnership between IAR Systems and Alif Semiconductor accelerates innovation in the embedded space through strong artificial intelligence (AI) and machine learning (ML) capabilities
https://www.iar.com/dev-dynamic-custom-objects/iar-systems-enables-powerful-ai-ml-applications-based-on-alif-semiconductors-microcontrollers-and-fusion-processors-62537440
IAR Systems enables early technology adoption of the AI-capable Arm Cortex-M55 core
Support for the latest Arm Cortex-M55 processor in IAR Embedded Workbench provides strong tools support for the new family and ensures future innovation in embedded applications
https://www.iar.com/dev-dynamic-custom-objects/iar-systems-enables-early-technology-adoption-of-the-ai-capable-arm-cortex-m55-core-a6b94be8
Tomi Engdahl says:
Is CodeGPT free?
Simply download the free extension, add your API key from popular AI providers like OpenAI, Google, Microsoft, Cohere, AI21, Anthropic, GPT4All, or HuggingFace, and start experiencing the benefits of AI-powered coding. One of the key features of CodeGPT is the ability to design and train your own AI Copilots.
https://www.capterra.in/software/1062768/codegpt
Tomi Engdahl says:
Amazon Q Developer is available for use in your code editor. Download a plugin or extension below and get started on the Amazon Q Developer Free Tier in a few minutes.
https://aws.amazon.com/q/developer/?gclid=EAIaIQobChMIt5zr3JSxigMVAA-iAx0enTaFEAAYASAAEgIgjfD_BwE&trk=45c2a23c-23fc-4f2e-b28a-4d8b6ef62ce7&sc_channel=ps&ef_id=EAIaIQobChMIt5zr3JSxigMVAA-iAx0enTaFEAAYASAAEgIgjfD_BwE:G:s&s_kwcid=AL!4422!3!698133085584!e!!g!!ai%20coding%20assistant!21048268977!166963732932
Tomi Engdahl says:
Copilot4Eclipse
Copilot4Eclipse (Copilot for Eclipse) is a free Eclipse plugin that professionally integrates the GitHub Copilot AI developer tools into your Eclipse IDE. Together Eclipse with the Copilot4Eclipse plugin provide you a powerful AI-assisted coding experience.
https://www.genuitec.com/products/copilot4eclipse/?gad_source=1&gclid=EAIaIQobChMI–HxiJWxigMVBhCiAx36wxIoEAAYAiAAEgIlnPD_BwE
Tomi Engdahl says:
The Ultimate AI Code Assistant – Try it for Free
Diffblue
https://www.diffblue.com › code_assistant
The Easiest and Fastest Way to Unit Test Your Code in IntelliJ. Ideal If You Want To Continuously Unit Test Quickly and Efficiently.
https://www.diffblue.com/developers/?utm_term=ai%20code%20assistant&utm_campaign=Search+-+WE+-+Developers&utm_source=google&utm_medium=cpc&hsa_acc=6887154342&hsa_cam=21913040106&hsa_grp=175869642612&hsa_ad=721782569163&hsa_src=g&hsa_tgt=kwd-1739103605752&hsa_kw=ai%20code%20assistant&hsa_mt=p&hsa_net=adwords&hsa_ver=3&gad_source=1&gclid=EAIaIQobChMI–HxiJWxigMVBhCiAx36wxIoEAAYAyAAEgKTpvD_BwE
Don’t write Java unit tests from scratch yourself – generate them! Write better code faster with unit test generation throughout the development process – locally and in CI.
Tomi Engdahl says:
AI code analysis | Eclipse Plugins, Bundles and Products
Eclipse Marketplace
AssistAI is an Eclipse IDE plugin that brings ChatGPT functionality into your development environment. This experimental plugin has been primarily tested with …
https://marketplace.eclipse.org/free-tagging/ai-code-analysis
Tomi Engdahl says:
Tag & Track AI Code
SonarSource
Scan AI Code with Sonar — Confidently integrate AI into your code by enforcing high standards of quality & security
AI-ASSISTED & QUALITY-ASSURED CODE
Trust your developers, verify your AI generated code
https://www.sonarsource.com/lp/solutions/ai-assurance-codefix/?s_campaign=SQ-EMEA-North-Nordics-Generic&s_content=AI&s_term=ai%20code%20generator&s_category=Paid&s_source=Paid%20Search&s_origin=Google&cq_src=google_ads&cq_cmp=21778746925&cq_con=166756376085&cq_term=ai%20code%20generator&cq_med=&cq_plac=&cq_net=g&cq_pos=&cq_plt=gp&gad_source=1&gclid=EAIaIQobChMI–HxiJWxigMVBhCiAx36wxIoEAMYASAAEgKuOPD_BwE
AI assistants like GitHub Copilot, Amazon Q, and Google Gemini boost developers’ productivity but can introduce security vulnerabilities and poor-quality code. To ensure code quality and security, developers and organizations adopt a “trust and verify” approach to AI-generated code. By providing developers and organizations with the tools to confidently integrate AI into their SDLC, Sonar is helping accelerate innovation safely and responsibly.
Tomi Engdahl says:
https://github.com/eclipsesource/ide-ai-assistant
Tomi Engdahl says:
Can Copilot build a library in C? Well…
https://www.youtube.com/watch?v=dH1AvQQDtiY
Given just a struct, GitHub Copilot builds a whole library in C.
I think this AI is great for intermediate or expert programmers but could be dangerous for newbies. If you are a new programmer using Copilot, consider making sure you grok the solutions it suggests otherwise you could A: stunt your growth as a programmer and B: accept low quality or buggy suggestions and then not know how to fix them.
Comments:
This is dangerous for newbies LOL
I have been using it and found it dangerous for myself, too… Sometimes it does strange things. For example I had to initialise 4 pieces of data, all using exactly the same params. So I filled out the first then tab-completed the next 3 but for some reason the last one was auto-completed by Copilot to a slightly different set of params that didn’t throw a compile error but broke my program.
Tomi Engdahl says:
Does GitHub Copilot work for C?
About GitHub Copilot and JetBrains IDEs
GitHub Copilot provides suggestions for numerous languages and a wide variety of frameworks, but works especially well for Python, JavaScript, TypeScript, Ruby, Go, C# and C++.
Getting code suggestions in your IDE with GitHub Copilot
Use GitHub Copilot to get code suggestions in your editor.
https://docs.github.com/en/copilot/using-github-copilot/getting-code-suggestions-in-your-ide-with-github-copilot
Tomi Engdahl says:
Can AI generate C code?
By providing detailed prompts and context, the AI generates optimized C code snippets tailored to your requirements.
Workik
AI-Powered C Code Generator: Your Customized Coding Partner. Try for free!
https://workik.com/ai-powered-c-code-generator
Tomi Engdahl says:
Yvonne Lau / Rest of World:
Experts say national security and immigration policies could deprive US companies of AI talent from China, which had 47% of the top AI researchers in 2022
China’s AI elite rethink their Silicon Valley dream jobs
The West may lose out in the talent race amid U.S. national security and immigration hurdles
https://restofworld.org/2024/china-us-immigration-policy-ai-talent/
“It’s simple. Chinese professionals who specialize in AI, if given the chance, definitely [prefer to] come to the U.S. to work for top companies,” Ming Chang, who works on AI and machine learning-related products for Meta in San Francisco, told Rest of World.
But intensifying U.S.-China tech competition and fears of Chinese industrial espionage have translated into tough-on-China security and immigration screenings that are posing practical challenges for Chinese diaspora tech workers. These hurdles could deprive North American tech companies of top AI talent, experts told Rest of World.
China produces nearly half of the world’s AI talent — compared to the U.S. which accounts for 18%. China has consistently ranked as the U.S.’ biggest and most important source of high-level international STEM workers.
“If you asked me a decade ago, I would say there are a lot of opportunities in China since everything moves very fast. It was definitely a good place for tech workers,” Zhou said. “These days, because of the geopolitical tensions, [tools from companies like] OpenAI are not accessible in China.” Chinese tech companies “have to do everything from the ground up” because of the U.S. export controls, he said.
Tomi Engdahl says:
https://hackaday.io/project/190480-jetson-tracking-cam
Tomi Engdahl says:
OPINION
Tekoäly edellyttää yhä nopeampia verkkoja
https://etn.fi/index.php/opinion/16974-tekoaely-edellyttaeae-yhae-nopeampia-verkkoja
Kestävä digitaalinen infrastruktuuri on kriittinen, jotta tietoliikenneverkot voidaan tehokkaasti valjastaa tekoälyinnovaatioiden ja pilvipohjaisten palveluiden tarpeisiin. Tekoälyyn liittyvien datarikkaiden sovellusten lisääntyvä kysyntä edellyttää tietoliikenneverkkoa, joka kykenee käsittelemään suuria tietomääriä alhaisella viiveellä, kirjoittaa Orange Businessin kumppaniratkaisuista vastaava Carl Hansson.
Tekoälyohjatut tietovirrat vaativat ketteryyttä ja joustavuutta useissa verkkoympäristöissä. Tämä tarkoittaa, että nykypäivän digitaalisten infrastruktuurien tulee pystyä käsittelemään täysin uudenlaista dataliikennettä.
Tekoälyn myötä datan hallinta muuttuu yhä hajautetummaksi, mikä vaikeuttaa turvallista tietojen siirtoa. Yritysten on varmistettava, että heillä on vahvat fyysiset ja sääntelyyn perustuvat suojaukset eri verkkoympäristöissä. Samalla verkkojen on täytettävä säädösten vaatimukset ja kyettävä mukautumaan niihin.
Verkkoja pitäisi myös pystyä hallitsemaan tehokkaasti. Tietoliikenneverkko voi myös auttaa välttämään tekoälyn käytön yleisiä haittoja, kuten hyökkäyksiä. Yrityksillä on oltava selkeä näkyvyys infrastruktuuriinsa, mukaan lukien tietoliikenneverkkoon, sekä tieto siitä, kuka hallitsee dataa ja mistä se tulee. Luotettava verkko luo pohjan myös tekoälyratkaisujen syötettävän datan luotettavuudelle.
Verkon ruuhkien hallinnan merkitys kasvaa, ja kun verkkoliikenne kasvaa, liikennemallit ja tietoliikenneverkon vaatimukset muuttuvat. Jos näitä ei hallita oikein, pullonkauloja ja viiveitä voi syntyä. Esimerkiksi globaalin kriisin aikana tietoliikenneverkon on oltava valmis täyttämään palvelutasosopimukset käyttäjien ja datan välisistä haasteista huolimatta.
Tekoälyn jatkaessa liiketoiminnan muokkaamista tietoliikenneverkkojen ja digitaalisten infrastruktuurien uudelleenajattelu tulee olemaan kriittistä menestyksen kannalta.
Tomi Engdahl says:
Cristina Criddle / Financial Times:
Q&A with Microsoft Chief Product Officer of Responsible AI Sarah Bird on generative AI, its impact on work, Copilots, OpenAI, AGI, AI agents, bias, and more
Microsoft’s Sarah Bird: Core pieces are still missing from artificial general intelligence
https://www.ft.com/content/aac74337-cb3f-43e7-894a-d85afedd3610
Chief product officer of ‘responsible AI’ says the focus needs to be on augmenting — not replicating — human capabilities
Sarah Bird’s role at technology group Microsoft is to ensure the artificial intelligence ‘Copilot’ products it releases — and its collaborative work with OpenAI — can be used safely. That means ensuring they cannot cause harm, treat people unfairly, or be used to spread incorrect or fake content.
Her approach is to draw on customer feedback from dozens of pilot programmes, to understand the problems that might emerge and make the experience of using AI more engaging. Recent improvements include a real time system for detecting instances where an AI model is ‘hallucinating’ or generating fictional outputs.
Here, Bird tells the FT’s technology reporter Cristina Criddle why she believes generative AI has the power to lift people up — but artificial general intelligence still struggles with basic concepts, such as the physical world.
Cristina Criddle: How do you view generative AI? Is it materially different to other types of AI that we’ve encountered? Should we be more cognisant of the risk it poses?
Sarah Bird: Yes, I think generative AI is materially different and more exciting than other AI technology, in my opinion. The reason is that it has this amazing ability to meet people where they are. It speaks human language. It understands your jargon. It understands how you are expressing things. That gives it the potential to be the bridge to all other technologies or other complex systems.
We can take someone who, for example, has never programmed before and actually allow them to control a computer system as if they were a programmer. Or you can take someone who, for example, is in a vulnerable situation and needs to navigate government bureaucracy, but doesn’t understand all the legal jargon — they can express their questions in their own language and they can get answers back in a way that they understand.
I think the potential for lifting people up and empowering people is just enormous with this technology. It actually speaks in a way that is human and understands in a way that feels very human — [that] really ignites people’s imagination around the technology.
We’ve had science fiction forever that shows humanoid AIs wreaking havoc and causing different issues. It’s not a realistic way to view the technology, but many people do. So, compared to all of the other AI technologies before, we see so much more fear around this technology for those reasons.
CC: It seems to be transformative for some tasks, especially in our jobs. How do you view the impact it will have on the way we work?
SB: I think that this technology is absolutely going to change the way people work. We’ve seen that with every technology. One of the perfect examples is calculators. Now, it’s still important in education for me to understand how to do that type of math, but day to day I’m not going to do it by hand. I’m going to use a calculator because it saves me time and allows me to focus my energy on what’s the most important.
We are absolutely seeing this in practice, [with generative AI], as well. One of the applications we released first was GitHub Copilot. This is an application that completes code. In the same way that it helps auto complete your sentences when you’re typing an email, this is autocompleting your code. Developers say that they’re going 40 per cent faster using this and — something that’s very, very important to me — they are 75 per cent more satisfied with their work.
We very much see the technology removing the drudgery, removing the tasks that you didn’t like doing, anyway — allowing everybody to focus on the part where they’re adding their unique differentiation, adding their special element to it, rather than the part that was just repeated and is something that AI can learn.
CC: OpenAI is a strategic partner of yours. It’s one of the key movers in the space. Would you say that your approaches to responsible AI are aligned?
SB: Yes, absolutely. One of the reasons early on that we picked OpenAI to partner with is because our core values around responsible AI and AI safety are very aligned.
Now, the nice thing about any partnership is we bring different things to the table. For example, OpenAI’s big strength is the core model development. They’ve put a lot of energy in advancing state of the art safety alignment in the model itself, where we are building a lot of complete AI applications.
CC: Do you think we’re close to artificial general intelligence?
SB: This is my personal answer, but I think AGI is a nongoal. We have a lot of amazing humans on this planet. And so, the reason I get out of bed every day is not to replicate human intelligence. It’s to build systems that augment human intelligence.
It’s very intentional that Microsoft has named our flagship AI systems ‘co-pilots’, because they’re about AI working together with a human to achieve something more. So much of our focus is about ensuring AI can do things well that humans don’t do well. I spend a lot more time thinking about that than the ultimate AGI goal.
CC: When you say AGI is a nongoal, do you still think it’s likely to happen?
SB: It’s really hard to predict when a breakthrough is going to come. When we got GPT4, it was a huge jump over GPT3 — so much more than anybody expected. That was exciting and amazing, even for people like myself that have worked in generative AI for a long time.
Will the next generation of models be as big of a jump? We don’t know. We’re going to push the techniques as far as we can and see what’s possible. I just take every day as it comes.
But my personal opinion is I think there are still fundamental things that have to be figured out before we could cross a milestone like AGI. I think we’ll really keep pushing in the directions we’ve gone, but I think we’ll see that run out and we’ll have to invent some other techniques as well.
CC: What do we need to figure out?
It still feels like there’s core pieces missing in the technology. If you touch it, it’s magical — it seems to understand so much. Then, there’s places where it feels like it doesn’t understand basic concepts
SB: It still feels like there’s core pieces missing in the technology. If you touch it, it’s magical — it seems to understand so much. Then, at the same time, there’s places where it feels like it doesn’t understand basic concepts. It doesn’t get it. An easy example is that it doesn’t really understand physics or the physical world.
For each of these core pieces that are missing, we have to go figure out how to solve that problem. I think some of those will need new techniques, not just the same thing we’re doing today.
CC: How do you think about responsibility and safety with these new systems that are meant to be our co-pilots, our agents, our assistant? Do you have to think about different kinds of risks?
SB: Everybody is really excited about the potential of agentic systems. Certainly, as AI becomes more powerful, we have the challenge that we need to figure out how to make sure it’s doing the right thing. One of the main techniques we use today — that you see in all of the co-pilots — is human oversight. You’re looking at whether or not you want to accept that email suggestion.
If the AI starts doing more complex tasks where you actually don’t know the right answer, then it’s much harder for you to catch an error.
That level of automation where you’re not actually watching, and [the AI is] just taking actions, it completely raises the bar in terms of the amount of errors that you can tolerate. You have to have extremely low amounts of those.
You could be taking an action that has real-world impact. So we need to look at a much broader risk space in terms of what’s possible.
On the agents front, we’re going to take it step by step and see where is it really ready, where can we get the appropriate risk-reward trade-off. But it’s going to be a journey to be able to realise the complete vision where it can do many, many different things for you and you trust it completely.
Tomi Engdahl says:
Jo joka kymmenes palkansaaja käyttää tekoälyä
Ilkka Ahtokivi
Julkaistu 17.12.2024 | 09:16
Päivitetty 17.12.2024 | 09:16
Tekoäly, Työelämä
Työolotutkimuksen mukaan uupumus työssä ja stressin kokemus on yleisintä 25–34-vuotiailla.
https://www.verkkouutiset.fi/a/jo-joka-kymmenes-palkansaaja-kayttaa-tekoalya/#9c1dc2d3
Tomi Engdahl says:
Tekoäly mullistaa suomalaista työelämää – ”Ei vain uhkakuva”
Anna Helakallio16.12.202414:40|päivitetty16.12.202414:40TekoälyTyöelämä
Solitan generatiivisesta tekoälystä vastaava Lasse Girs kertoo yhtiön tiedotteessa, että merkittävä osa työelämässä olevista suomalaisista suhtautuu tekoälyyn positiivisesti.
https://www.tivi.fi/uutiset/tekoaly-mullistaa-suomalaista-tyoelamaa-ei-vain-uhkakuva/f2b013a4-6df4-4fb7-94b5-69f5eadeb00e
Tomi Engdahl says:
OpenAI’s Sora Is Generating Videos of Real People, Including This Unintentionally Demonic Version of Pokimane
Why does Sora know who Pokimane is?
https://futurism.com/openai-sora-pokimane-real-people
Tomi Engdahl says:
Googlen tekoäly varoittaa sään äärioloista hätkähdyttävän nopeasti
Perinteisiltä sääennustemalleilta kestää 15 päivän ennusteen luomisessa useita tunteja.
https://www.kauppalehti.fi/uutiset/googlen-tekoaly-varoittaa-saan-aarioloista-hatkahdyttavan-nopeasti/0de75556-5eac-4a5e-8c55-f4c5465d6d8f
Teknologiayhtiö Google Deepmindin uusi tekoälymalli Gencast on tarkkuudeltaan kilpailukykyinen perinteisten sääennustemallien kanssa. Gencast onnistui jopa voittamaan johtavan ennustemallin, kun sille syötettiin vuodelta 2019 peräisin olevaa dataa, The Verge kertoo.
Tekoäly ei korvaa perinteisiä sääennusteita vielä lähitulevaisuudessa. Teknologiaa voidaan kuitenkin käyttää kätevänä lisätyökaluna. Gencast on vain yksi kehitteillä olevista tekoälytyökaluista, jotka saattavat mahdollistaa entistä tarkemman sään ennustamisen tulevaisuudessa.
Tomi Engdahl says:
Google’s AI weather prediction model is pretty darn good / The company says its AI model outperformed a traditional forecasting system.
https://www.theverge.com/2024/12/7/24314064/ai-weather-forecast-model-google-deepmind-gencast
Tomi Engdahl says:
‘Shockingly real’ AI Santa is free to use, will put Mall Santas everywhere out of jobs
News
By Mark Tyson published December 15, 2024
AI Santa uses the Conversational Video Interface (CVI) from Tavus.
https://www.tomshardware.com/tech-industry/artificial-intelligence/shockingly-real-ai-santa-is-free-to-use-will-put-mall-santas-everywhere-out-of-jobs
Tomi Engdahl says:
Microsoft valtaa suositun näppäinyhdistelmän Copilotin käyttöön
Joona Komonen17.12.202420:03WindowsTekoäly
Copilot käyttää jatkossa useiden sovelluksien suosimaa alt+space-pikakomentoa.
https://www.tivi.fi/uutiset/microsoft-valtaa-suositun-nappainyhdistelman-copilotin-kayttoon/da8b7446-7229-4863-a60d-72147c9f94d2
Tomi Engdahl says:
Suomen toinen kvanttitietokone on valmistunut
https://www.vttresearch.com/fi/uutiset-ja-tarinat/suomen-toinen-kvanttitietokone-valmistunut
VTT ja suomalainen kvanttialan yritys IQM Quantum Computers ovat saaneet valmiiksi Suomen toisen kvanttitietokoneen. Uusi 20 kubitin kvanttitietokone on osoitus vahvasta kansallisesta teknologiaosaamisesta sekä kyvykkyydestä skaalata kvanttitietokoneita yhä suuremmaksi ja paremmaksi ratkaisemaan monimutkaisia ongelmia.
Tomi Engdahl says:
Hayden Field / CNBC:
OpenAI debuts a way to talk to ChatGPT by dialing 1-800-CHATGPT for 15 minutes of free access per month in the US or messaging the number via WhatsApp globally — OpenAI on Wednesday rolled out a new way to talk to its viral chatbot: 1-800-CHATGPT. — By dialing the U.S. number …
AI Effect
OpenAI makes ChatGPT available for phone calls and texts
https://www.cnbc.com/2024/12/18/openai-makes-chatgpt-available-for-phone-chats.html
OpenAI on Wednesday rolled out a new way to talk to its viral chatbot: 1-800-CHATGPT.
U.S. users can dial the number for 15 minutes of free access per month.
Any user globally can message the number via WhatsApp.
OpenAI is giving users a new way to talk to its viral chatbot: 1-800-CHATGPT.
By dialing the U.S. number (1-800-242-8478) or messaging it via WhatsApp, users can access an “easy, convenient, and low-cost way to try it out through familiar channels,” OpenAI said Wednesday. At first, the company said callers will get 15 minutes free per month.
The news follows a barrage of updates from OpenAI as part of a 12-day release event. The most notable announcement was the official rollout of Sora, OpenAI’s buzzy AI video-generation tool.
OpenAI closed its latest funding round in October at a valuation of $157 billion. The company also received a $4 billion revolving line of credit, bringing its total liquidity to more than $10 billion.
Tomi Engdahl says:
Frederic Lardinois / TechCrunch:
GitHub offers Copilot in VS Code for free with 2,000 code completions and 50 chat messages per month; GitHub now has 150M developers, up from 100M in early 2023 — Microsoft-owned GitHub today announced a free version of its popular Copilot code completion/AI pair programming tool …
GitHub launches a free version of its Copilot
https://techcrunch.com/2024/12/18/github-launches-a-free-version-of-its-copilot/
Microsoft-owned GitHub announced on Wednesday a free version of its popular Copilot code completion/AI pair programming tool, which will also now ship by default with Microsoft’s popular VS Code editor. Until now, most developers had to pay a monthly fee, starting at $10 per month, with only verified students, teachers, and open source maintainers getting free access.
GitHub also announced that it now has 150 million developers on its platform, up from 100 million in early 2023.
“My first project [at GitHub] in 2018 was free private repositories, which we launched very early in 2019,” GitHub CEO Thomas Dohmke told me in an exclusive interview ahead of Wednesday’s announcement. “Then we had kind of a v2 with free private organizations in 2020. We have free [GitHub] Actions entitlements. I think at my first Universe [conference] as CEO, we announced free Codespaces. And so it felt natural, at some point, to get to the point where we also have a completely free Copilot, not just one that is for students and open source maintainers.”
There are some limitations to the free version, which is geared toward occasional users, not major work on a big project.
The AI editor for everyone
https://github.com/features/copilot
Tomi Engdahl says:
Shirin Ghaffary / Bloomberg:
Source: Perplexity raised $500M led by Institutional Venture Partners at a $9B valuation earlier in December, up from a $3B valuation in June 2024 — The company’s valuation has tripled since June. … The round was led by Institutional Venture Partners and completed earlier this month …
https://www.bloomberg.com/news/articles/2024-12-18/ai-startup-perplexity-closes-funding-round-at-9-billion-value
Tomi Engdahl says:
Financial Times:NEW
Alejandro Mayorkas, the US DHS’ outgoing secretary, says Europe’s “adversarial” relationship with tech companies is hampering a global approach to AI regulation — Alejandro Mayorkas warns tensions between US and Europe have grown over differences in regulating top AI companies
https://www.ft.com/content/22fc36b8-5707-460c-9591-02f7b6f68d65
Tomi Engdahl says:
Financial Times:
Omdia estimates Microsoft bought 485K of Nvidia’s Hopper GPUs in 2024, ByteDance and Tencent bought ~230K each, Meta bought 224K, and Tesla/xAI bought ~200K
https://www.ft.com/content/e85e43d1-5ce4-4531-94f1-9e9c1c5b4ff1
Tomi Engdahl says:
Bloomberg:
SandboxAQ, which aims to apply quantum tech and techniques to AI, raised $300M+ from Alger, Yann LeCun, and others at a $5.6B+ valuation to hire more engineers
https://www.bloomberg.com/news/articles/2024-12-18/ai-startup-sandboxaq-raises-funds-at-over-5-6-billion-valuation
Tomi Engdahl says:
Artificial Intelligence
AI Regulation Gets Serious in 2025 – Is Your Organization Ready?
While the challenges are significant, organizations have an opportunity to build scalable AI governance frameworks that ensure compliance while enabling responsible AI innovation.
https://www.securityweek.com/ai-regulation-gets-serious-in-2025-is-your-organization-ready/
Tomi Engdahl says:
I Built a Neural Network from Scratch
https://www.youtube.com/watch?v=cAkMcPfY_Ns
I’m not an AI expert by any means, I probably have made some mistakes. So I apologise in advance
Also, I only used PyTorch to test the forward pass. Apart from that, everything else is written in pure Python (+ use of Numpy).
How I Learned This: https://nnfs.io/ (by the awesome @sentdex )
Tomi Engdahl says:
PyTorch in 100 Seconds
https://www.youtube.com/watch?v=ORMx45xqWkA
PyTorch is a deep learning framework for used to build artificial intelligence software with Python. Learn how to build a basic neural network from scratch with PyTorch 2.
Tomi Engdahl says:
Introducing NVIDIA Jetson Orin™ Nano Super: The World’s Most Affordable Generative AI Computer
https://m.youtube.com/watch?v=S9L2WGf1KrM
Tomi Engdahl says:
The NVIDIA Jetson Orin™ Nano Super Developer Kit’s performance, compact size, and low cost are redefining generative AI for small edge devices.
At just $249, it provides developers, students, and builders with the most affordable and accessible platform, backed by the support of NVIDIA AI software and a broad AI software ecosystem.
Learn more: https://nvda.ws/3ZVdySx
Tomi Engdahl says:
Captivating Remake: Röyksopp’s ‘Stay Awhile’ Recreated with AI Technology
https://www.youtube.com/watch?v=X7KpKaYO4LU
I have been a fan of all 3 of Royksopp’s last three albums, Profound Mysteries. As a matter of fact, they ended up on my top artists of 2023 according to YouTube. I wanted to see if I could create a video using only AI generated characters for one of my favorite songs, Stay Awhile.
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I did not want AI to create the video for me, but rather employ different AI tools to create the characters and to animate different scenes. I would then take those images and videos and edit an entire video using Premier Pro.
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All in all, I generated over 500 different characters and videos animations for this video using Midjourney, Kaiber, LeiaPix and Runway ML. For the most part, 98% of the characters were created using Midjourney because I felt as if Midjourney created the most realistic characters. Runway ML and Leiapix were used for the motion, with Leiapix being used for the 3D animation and Runway ML for the motion using their motion brush.
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I edited using Premier Pro. Because Midjourney and Runway ML create rather cinematic coloring in their images, Color grading was kept to a minimum. I used Lumetrix with Matrix Green color grading instead of my usual CinemaGrade.
Tomi Engdahl says:
Artificial intelligence can tell Scotch whisky from American and identify its strongest constituent aromas more reliably than human experts – by using data rather than tasting the drinks.
AI beats human experts at distinguishing American whiskey from Scotch
Using descriptions of flavours or chemical data, artificial intelligence can tell apart whiskies from different countries and identify their constituent aromas
https://www.newscientist.com/article/2460910-ai-beats-human-experts-at-distinguishing-american-whiskey-from-scotch/?utm_medium=social&utm_campaign=echobox&utm_source=Facebook&fbclid=IwZXh0bgNhZW0CMTEAAR2cGaABYdKSiIT42qPk9BlnZsTGy6nDVsAlm_ikPmBf-n2gYiRo6GCAC70_aem_jONgQufBHhn674giP3AcaQ#Echobox=1734627736-1
Artificial intelligence can tell Scotch whisky from American whiskey and identify its strongest constituent aromas more reliably than human experts – by using data rather than tasting the drinks.
Andreas Grasskamp at the Fraunhofer Institute for Process Engineering and Packaging IVV in Germany and his colleagues trained an AI molecular odour prediction algorithm called OWSum on descriptions of different whiskies.
Tomi Engdahl says:
AI can tell which chateau Bordeaux wines come from with 100% accuracy
A machine-learning algorithm was able to tell which estate 80 Bordeaux red wines came from with 100 per cent accuracy by assessing their chemical signatures
https://www.newscientist.com/article/2406286-ai-can-tell-which-chateau-bordeaux-wines-come-from-with-100-accuracy/
Tomi Engdahl says:
Tasting IS data…
Is there nothing that won’t be ruined by this puritanical AI dictatorship?
Tomi Engdahl says:
Kyle Wiggers / TechCrunch:
Google releases Gemini 2.0 Flash Thinking, an experimental “reasoning” model that “explicitly shows its thoughts” and can use them to strengthen its reasoning — Google has released what it’s calling a new “reasoning” AI model — but it’s in the experimental stages …
Google releases its own ‘reasoning’ AI model
https://techcrunch.com/2024/12/19/google-releases-its-own-reasoning-ai-model/
Google has released what it’s calling a new “reasoning” AI model — but it’s in the experimental stages, and from our brief testing, there’s certainly room for improvement.
The new model, called Gemini 2.0 Flash Thinking Experimental (a mouthful, to be sure), is available in AI Studio, Google’s AI prototyping platform. A model card describes it as “best for multimodal understanding, reasoning, and coding,” with the ability to “reason over the most complex problems” in fields such as programming, math, and physics.
In a post on X, Logan Kilpatrick, who leads product for AI Studio, called Gemini 2.0 Flash Thinking Experimental “the first step in [Google’s] reasoning journey.” Jeff Dean, chief scientist for Google DeepMind, Google’s AI research division, said in his own post that Gemini 2.0 Flash Thinking Experimental is “trained to use thoughts to strengthen its reasoning.”
“We see promising results when we increase inference time computation,” Dean said, referring to the amount of computing used to “run” the model as it considers a question.