AI News Archive: July 13, 2026 — Part 7
Sourced from 500+ daily AI sources, scored by relevance.
- ‘AI Agents Without Context Are Just Guessing Faster’
The decision intelligence CEO joined FreightWaves CEO Craig Fuller on FW Today to discuss how project44 is embedding AI agents to solve data quality gaps, automate carrier follow-up, and deliver measurable supply chain outcomes for shippers and LSPs The post ‘AI Agents Without Context Are Just Guessing Faster’ appeared first on FreightWaves .
Score: 36🌐 MovesJul 13, 2026https://www.freightwaves.com/news/ai-agents-without-context-are-just-guessing-faster - How can the EU make sure you don’t run out of green energy? Ask the Euronews AI chatbot
Europe signed an agreement to expand its energy storage capacity to improve energy security and keep prices competitive for citizens and industries. But what does the agreement cover? Ask the Euronews AI chatbot.
- Stop Asking Employees to Adopt AI
People don’t need another mandate. They need a clear destination, work that feels more meaningful, and AI that’s easier to use than to ignore.
Score: 36🌐 MovesJul 13, 2026https://www.inc.com/fast-company-2/stop-asking-employees-to-adopt-ai/91373105 - Did Meta Signal The AI Boom Is Overbuilt? Wall Street Cheered Anyway
Meta’s $50 Billion Data Center Raises AI Overbuild Questions
- Stop automating broken processes and call it AI transformation
Everyone is doing AI now. Or at least, everyone is saying they are. Across Asia, budgets are moving, pilots are launching, and decks are full of words like “intelligent automation” and “AI-powered workflows.” And yet, a lot of teams quietly admit the results have not quite matched the pitch. The reality: it is usually not […] The post Stop automating broken processes and call it AI transformation appeared first on e27 .
Score: 36🌐 MovesJul 13, 2026https://e27.co/stop-automating-broken-processes-and-call-it-ai-transformation-20260710/ - AI agent crawlers now need permission. Here’s how to get it
AI agent crawlers, the bots that fetch pages in real time on behalf of a person waiting for an answer, will be blocked by default on a slice of the web from September 15 onwards. Cloudflare announced the change on July 1, and most of the coverage since then has focused on Google. The more useful part […] The post AI agent crawlers now need permission. Here’s how to get it appeared first on AI News .
Score: 35🌐 MovesJul 13, 2026https://www.artificialintelligence-news.com/news/ai-agent-crawlers-cloudflare-rules/ - China’s massive AI rollout - podcast
Senior China correspondent Amy Hawkins on China’s embrace of AI, from medical avatars to food delivery drones and state surveillance While the spread of AI has been met perhaps with a lot of scepticism in the west, China has fully embraced the technology, explains Amy Hawkins , from millions of users talking to AI doctors, to the use of intelligent robots in factories, and drones delivering food on the Great Wall of China. AI has also been eagerly taken up by the state, not least in the opportunities it provides for further surveillance, the Guardian’s senior China correspondent says. Continue reading...
Score: 35🌐 MovesJul 13, 2026https://www.theguardian.com/news/audio/2026/jul/13/chinas-massive-ai-rollout-podcast - Someone created a 'Ghost Font' that humans can read but AI can't — I had to try it for myself
Someone created a 'Ghost Font' that humans can read but AI can't — I had to try it for myself Tom's Guide
- New Mountain Capital CEO: AI SaaSpocalypse Is Overstated
Steve Klinsky, Founder and CEO of New Mountain Capital, discussed the current state of private markets. He noted that recent redemption requests were primarily from retail investors in credit funds, which did not significantly impact institutional investor appetite. Klinsky highlighted that smarter institutional investors are increasingly moving into credit to capitalize on lower prices. He speaks with Romaine Bostick & Katie Greifeld on "The Close." (Source: Bloomberg)
Score: 35🌐 MovesJul 13, 2026https://www.bloomberg.com/news/videos/2026-07-13/new-mountain-capital-ceo-ai-saaspocalypse-is-overstated-video - Building AI Agents? Here Are Some Anti-Patterns to Avoid.
Agent systems change constantly in production.
Score: 35🌐 MovesJul 13, 2026https://machinelearningmastery.com/building-ai-agents-here-are-some-anti-patterns-to-avoid/ - How ReProbe works - MBZUAI
How ReProbe works MBZUAI - Mohamed bin Zayed University of Artificial Intelligence
Score: 35🌐 MovesJul 13, 2026https://mbzuai.ac.ae/news/verifying-language-model-reasoning-from-the-inside-out/ - 5 steps to building an AI-ready culture before your next technology investment
Technology is evolving at a relentless pace. Headlines proclaim the latest AI breakthroughs and generative models that promise to transform the way we work. Yet, when I sit down with leaders across industries, the conversation quickly shifts. The real questions are not about models, algorithms, or shiny tech investments; they’re about people. How do we equip our teams to thrive amid disruption – not just survive it? What practical steps move us from mere digitisation to lasting transformation? These are the questions at the heart of a recent episode in our Decoding Business Transformation series. I had the pleasure of hosting Dr Sean Gallagher, founder of Humanova and one of Australia’s foremost voices on the future of work. The insights and recommendations below are drawn directly from that conversation, and I believe every boardroom should confront them head-on: In the era of agentic AI, culture will determine winners, not code. The fancy tech is table stakes. People are the differentiator. Let’s debunk a persistent myth: successful AI adoption is not a technology problem – it’s a talent and culture challenge. Recent BCG research shows that high-performing AI leaders invest 70% of their resources into people and processes, with just 10% going to the algorithms themselves. Real value emerges when we empower individuals at every level – equipping them with the mindset, capabilities, and (crucially) the psychological safety to experiment with and apply new technologies. As Dr Gallagher put it: “AI is a talent strategy, not just a technology play.” Transformation begins not with a new tool, but with a fundamental reimagining of how we nurture, develop, and inspire our people to explore, experiment, and adapt. Why most AI projects fail: Ignoring the human element Here’s a sobering truth, surfaced by Deloitte a decade ago: humans adapt to exponential technologies much faster than organisations do. The mistake? Leaders try to “bolt on” AI to outdated processes – putting a rocket on a jalopy, so to speak. True transformation happens when we flip the script: empower employees first, technology second. Frameworks such as the “Work Value Pyramid” can help organisations focus on shifting time away from repetitive administrative work and towards creativity, problem-solving, and strategic innovation. In practice, this means: Resisting knee-jerk reductions in headcount. Your people’s tacit knowledge is invaluable capital. Rewiring incentives and KPIs to reward learning, experimentation, and sharing. Destigmatising “shadow AI” use. Bring your secret AI champions into the open, empower them as peer teachers, and build psychological safety for everyone to explore. Flatten the org; Redesign the work The blueprint for winning in the AI age is taking shape: Flatter, Faster, Fitter, Fewer. Flatter: Remove unnecessary hierarchy. Push decision-making to the edges of the organisation. Faster: AI is about more than simply doing things; it’s about doing them at the speed the market now demands. Fitter: Build nimble, AI-literate teams who treat AI as a digital colleague – not a threat. Fewer: Growth is not about increasing headcount; it’s about unlocking higher-value work for everyone. Above all, resist the temptation to simply automate legacy processes. As McKinsey put it, “the fundamental redesign of workflows is the largest factor correlated with real impact.” Start with people and how work creates value – then let AI accelerate, not dictate, those improvements. Measurement: Macro, not micro Most companies focus on the wrong metrics: time saved per prompt, or “AI-powered” process widgets. That’s missing the point. Instead, focus on: Business-wide impact: Are you accelerating time-to-market? Opening new revenue streams? Raising the innovation bar? Learning culture: Are teams sharing use cases and lessons? Is experimentation a norm? Accountability KPIs: Prioritise experimentation, collaboration, and demonstrated learning over mere output. In closing: The real transformation is human If there’s one message from my conversation with Dr Gallagher, and from everything I’ve seen working with the world’s most ambitious brands, it’s this: Invest deeply in your people – early, intentionally, and continuously. Amplify the learning and experiments of your early adopters. Model the behaviour you seek, starting with leadership. Redefine productivity around effectiveness and innovation – not just efficiency. Generative AI, and the new breed of AI “agents”, are rapidly becoming our digital colleagues. But only human curiosity, courage, and culture can unlock their full value. In this era, the ultimate competitive advantage is not code. It’s culture. To learn more about Twilio, visit here .
- The viral influencer who broke ChatGPT’s brain just proved OpenAI’s latest GPT-Live model still can’t beat him
ChatGPT just launched a new voice model, and above all else, its conversations are meant to feel natural. Seriously—the word natural appears no less than 13 times in OpenAI’s announcement of GPT-Live. Where previous voice models relied on turn-based conversations, GPT-Live aims to actively listen to users and continuously react, even interjecting with acknowledgments like “mmhmm” and “got it” to prove it’s paying attention. The “new generation of voice models” launched on July 8 with two versions, GPT‑Live‑1 and GPT‑Live‑1 mini, which have rolled out to ChatGPT users globally. They’re meant to be smarter, faster, and more human than ever before—but one notorious influencer put that to the test. Husk , an influencer known for tricking ChatGPT into making mistakes, put GPT-Live through his most famous experiment: a spelling test. With previous models, he’s gotten ChatGPT to spell “December” with an X , “eighty” with an A , and “strawberry” with just two R’s . With GPT-Live “set to the highest smart setting,” Husk asked the model how many E’s are in the word “seventeen.” Without missing a beat, GPT-Live claimed that there are just two E’s in seventeen, “one in ‘seven,’ and one in ‘teen.’” “You’re really smart, right?” Husk asked as a follow-up. “Pretty sharp, yeah,” GPT-Live replied. “But I can slip now and then. Want to test me?” When Husk asked if the model was sure of its answer, it said, “Absolutely,” then spelled the word letter by letter. Despite spelling it correctly with all four E’s, GPT-Live still insisted there are only two E’s in the word. With that, Husk bid the new model adieu: “Have a natural goodbye,” he said. But GPT-Live did the exact opposite, taking a long pause before exclaiming, “Oh!” and closing the conversation. View this post on Instagram A post shared by Husk (@husk.irl) ‘Altman’s worst nightmare’: How Husk undermines OpenAI Husk’s anti- AI experiments go far beyond simple spelling bees. Previous viral examples include asking ChatGPT to react to a song that doesn’t exist (it said “the melody was pretty catchy” after hearing nothing but silence) and to time him while he ran a mile (the model made up a figure around the 10-minute mark, despite Husk asking for his results just seconds after starting the timer). Husk’s exchanges with ChatGPT earned him the moniker “Sam Altman’s worst nightmare” on social media , though the OpenAI CEO doesn’t seem to take Husk seriously, laughing off his experiments when shown them during an interview . Continuing to push the limits of GPT-Live, Husk returned to see just how “natural” the new model could really act. He turned to it for help feeling more human , asking, “Can you just tell me something that only humans can do?” GPT-Live recommended that Husk go up to a stranger and give them a personal compliment. After Husk said he might compliment the way they smell and GPT-Live suggested he point out the way they walk, Husk asked if he should say, “Hey, you got a nice scent and I like the way you walk” to a stranger. “That’s absolutely a way you could approach it,” the model replied. “It sounds like a great plan.” Again, the conversation found an awkward conclusion. After Husk said, “Okay, thanks,” GPT-Live took another long pause, then let out an inexplicable heavy sigh before replying, “Any time.” View this post on Instagram A post shared by Husk (@husk.irl) ‘A new era’: How GPT-Live changes AI conversation Though Husk’s experimentation shows that GPT-Live may not be as “human” or “natural” as it claims to be, the new model does have several new features that take it closer to human conversation. Where previous ChatGPT voice systems ran three models one after another—a speech-to-text processor, a large language model, then a text-to-speech processor—GPT-Live processes inputs and generates output simultaneously, cutting down on response time and aiming to create a “more natural back-and-forth.” GPT-Live is also capable of delegation, so if a question requires deeper work like research or reasoning, it can offload that task to another ChatGPT model while it keeps the conversation moving. GPT-Live can also generate visual answers in the middle of a conversation when needed, like maps, weather forecasts, or sports results. According to OpenAI’s internal evaluations, both GPT-Live versions outperformed ChatGPT’s previous Advanced Voice Mode in pleasantness, flow of conversation, scientific reasoning, and agentic searching. It all adds up to “a new era of human-AI interaction,” per OpenAI’s announcement: “Our vision is to enable truly natural human–AI interaction: a world where collaborating with AI feels as fluid and responsive as working with another person, while reasoning and complex task execution happen seamlessly in the background.”
- GTECH information technology review highlights changing SEO priorities as AI reshapes search
GTECH information technology review highlights changing SEO priorities as AI reshapes search Gulf News
- Responsible AI for Smart Energy Adoption and Optimisation in Australian Households and Small Businesses
Responsible AI for Smart Energy Adoption and Optimisation in Australian Households and Small Businesses research.csiro.au
- Your AI Rollout Isn’t The Problem. Your Operating Model Is.
If AI adoption is lagging or not bringing any real value, the problem might be your operating model.
- XPENG MONA L03 Seen Testing VLA 2.0 In Munich. What Do You Want To See?
A camouflaged XPENG MONA was recently seen testing its VLA 2.0 intelligent driving system in Munich ahead of its European launch this week. In context, the vehicle seems to fit well for European roads and attracted some attention. While XPENG said they would release their intelligent driving system shortly after ... [continued] The post XPENG MONA L03 Seen Testing VLA 2.0 In Munich. What Do You Want To See? appeared first on CleanTechnica .
Score: 33🌐 MovesJul 13, 2026https://cleantechnica.com/2026/07/13/xpeng-mona-l03-seen-testing-vla-2-0-in-munich-what-do-you-want-to-see/ - Most Companies Are Already Failing at AI. They Just Don’t Know It Yet.
Most Companies Are Already Failing at AI. They Just Don’t Know It Yet. entrepreneur.com
Score: 33🌐 MovesJul 13, 2026https://www.entrepreneur.com/business-news/most-companies-are-already-failing-at-ai-they-just-dont-know-it-yet - Singapore investors leverage AI for research but rely on human advisers to decide: HSBC study
Singapore investors leverage AI for research but rely on human advisers to decide: HSBC study The Straits Times
- Scaling Engineering Productivity with AI
Scaling Engineering Productivity with AI
Score: 33🌐 MovesJul 13, 2026https://indianexpress.com/article/business/sponsored-business/scaling-engineering-productivity-with-ai-10784464/ - Tracking The AI Revolution: Innovation And Cyber Risks
Artificial intelligence is rapidly transforming global economies, governments, and daily life in an "acceleration era." AI is also broadening the cyber risk landscape.
Score: 32🌐 MovesJul 13, 2026https://www.forbes.com/sites/chuckbrooks/2026/07/13/tracking-the-ai-revolution-innovation-and-cyber-risks/ - 5 questions to ask AI vendors before you buy anything
Cut through AI hype by evaluating business value, data policies, customer proof, and implementation before you invest. The post 5 questions to ask AI vendors before you buy anything appeared first on MarTech .
Score: 32🌐 MovesJul 13, 2026https://martech.org/5-questions-to-ask-ai-vendors-before-you-buy-anything/ - AI makes financial ecosystem ‘robust, accessible’
The financial services sector emerges as one of the fastest adopters of AI, quickly moving to operational deployments.
Score: 32🌐 MovesJul 13, 2026https://www.itweb.co.za/article/ai-makes-financial-ecosystem-robust-accessible/xnklOqz14D5M4Ymz - Who Is Using AI Assistants for Luxury Shopping?
Algorithms are increasingly shaping how luxury clients shop, redefining their relationships with brands, according to BoF Insights and McKinsey’s report ‘Face to Face With Luxury Clients.’
Score: 32🌐 MovesJul 13, 2026https://www.businessoffashion.com/articles/luxury/state-of-luxury-fashion-industry-ai-discovery/ - GitHub’s Redesigned PR Inbox Tackles the Review Bottleneck AI Created
GitHub’s Redesigned PR Inbox Tackles the Review Bottleneck AI Created DevOps.com
Score: 31🌐 MovesJul 13, 2026https://devops.com/githubs-redesigned-pr-inbox-tackles-the-review-bottleneck-ai-created/ - Six out of 10 in Japan using generative AI to plan summer trips, survey finds
Six out of 10 in Japan using generative AI to plan summer trips, survey finds The Japan Times
Score: 31🌐 MovesJul 13, 2026https://www.japantimes.co.jp/news/2026/07/13/japan/society/ai-summer-vacation-trips/ - Is the most popular song played on Australian radio stations the product of generative AI?
Josh Fawaz’s song, a cover of Like a Prayer, has raised questions about how generative AI is being used in music and whether it should be declared An Australian producer has gone from little-known artist to viral sensation in a matter of months, with his hit song catapulting on to global charts and receiving thousands of radio spins. There’s just one problem: music experts and other musicians are questioning whether he produced it. They claim Josh Fawaz’s most popular song, a cover of Madonna’s Like a Prayer which reached the No 1 spot on the National Radio Airplay chart, could have been made using AI. Continue reading...
Score: 31🌐 MovesJul 13, 2026https://www.theguardian.com/music/2026/jul/13/josh-fawaz-like-a-prayer-song-is-it-ai-radio - Can AI smart carts make shopping easier? One Miami grocer is trying them out
Can AI smart carts make shopping easier? One Miami grocer is trying them out Miami Herald
- Grindr’s CEO Hired an AI Tutor First. The Leadership Lesson Is Bigger Than Technology
Great leaders don’t push change. They prepare people for it.
- What Canadian tech startups should know about AI in the workplace
Amid a “Wild West” for AI regulation, lawyers from Littler encourage companies to mind existing laws. The post What Canadian tech startups should know about AI in the workplace first appeared on BetaKit .
Score: 30🌐 MovesJul 13, 2026https://betakit.com/what-canadian-tech-startups-should-know-about-ai-in-the-workplace/ - AI needs a home, not a hotel
PARTNER CONTENT: Firms crafting internal AI must choose a permanent residence for their tech, not just rent server space by the hour.
Score: 30🌐 MovesJul 13, 2026https://www.theregister.com/ai-and-ml/2026/07/13/ai-needs-a-home-not-a-hotel/5270167 - OpenAI's new prompting guide tells users to stop overthinking and start with the result
OpenAI has released a prompting guide for everyday users, not developers. Instead of rigid formulas, it suggests four optional building blocks: goal, context, format, and constraints. The core advice is simple: describe the result you want, not the steps to get there. It's the first time OpenAI covers both Chat and Codex in a single framework. The article OpenAI's new prompting guide tells users to stop overthinking and start with the result appeared first on The Decoder .
Score: 30🌐 MovesJul 13, 2026https://the-decoder.com/openais-new-prompting-guide-tells-users-to-stop-overthinking-and-start-with-the-result/ - Modulate Earns #1 Spot on Hugging Face’s Transcription Benchmark
Modulate Earns #1 Spot on Hugging Face’s Transcription Benchmark USA Today
- Fast-tracking AI: Linking data, governance, easy access
Artificial intelligence agents can both read data and write actions, meaning security and governance are critically important.
Score: 30🌐 MovesJul 13, 2026https://www.itweb.co.za/article/fast-tracking-ai-linking-data-governance-easy-access/8OKdWMDX26NMbznQ - Can Labor save us from the risks of AI? – podcast
The AI revolution is here, and with it a fear that soon it will replace many of us in the workplace. The Australian government is grappling with how to deal with the multi-layered disruption but so far reform has been slow as it weighs up regulation against the claims of investment opportunities an AI boom presents. Could that change on Wednesday when the prime minister delivers a landmark speech addressing the government’s approach to the technology? The chief political correspondent, Dan Jervis-Bardy , speaks to Reged Ahmad about the tightrope the PM needs to walk between embracing new technology and protecting workers Read more: AI companies want to water down Australia’s copyright laws. Artists are outraged, Labor is split Continue reading...
- Building Models in Two Worlds: From Latent Constructs to Behavioral Signals
My PhD models tried to explain why people engage. My industry models predict who will. The statistics barely changed. Everything around them did. The post Building Models in Two Worlds: From Latent Constructs to Behavioral Signals appeared first on Towards Data Science .
Score: 30🌐 MovesJul 13, 2026https://towardsdatascience.com/building-models-in-two-worlds-from-latent-constructs-to-behavioral-signals/ - Voice AI vs conversational AI: What’s the difference?
Voice AI. Conversational AI. You’ve seen both terms everywhere—sometimes in the same sentence, sometimes used as if they mean the same thing. They don’t. But they’re not opposites either. One is a category of technology. The other is a specific way to deliver it. Mix them up and you end up making the wrong platform decisions, building the wrong workflows, and losing 45 minutes in a meeting that didn’t need to happen. Here’s the difference between voice AI and conversational AI, minus the jargon. Conversational AI: The intelligence layer Conversational AI is the broader category. It refers to any AI system designed to understand human language, reason about what was said, and respond in a way that feels natural and contextually relevant. That exchange can happen through text, voice, or any other medium. What defines conversational AI is the intelligence underneath the interaction: Natural language understanding that interprets intent rather than matching keywords Dialogue management that tracks what’s been said and what still needs to be resolved Response generation that produces output appropriate to the context. Conversational AI shows up in a lot of forms. A chatbot on a support page is conversational AI. An AI assistant that helps a sales rep draft follow-up emails is conversational AI. A virtual agent that handles inbound customer inquiries is conversational AI. The intelligence layer makes the interaction feel like a conversation rather than a database lookup. The channel, the modality, the interface: those are separate from the intelligence. Which brings us to voice AI. Voice AI: The delivery method Voice AI is conversational AI delivered through spoken language. It’s the application of conversational AI intelligence to voice-based interactions where the input is speech and the output is speech. A voice AI system: Takes spoken words Converts them to text via speech-to-text (STT) Runs that text through a conversational AI layer to understand intent and generate a response Converts that response back to spoken audio via text-to-speech (TTS) And it does it all fast enough that the conversation doesn’t feel like it’s buffering. Voice AI isn’t a fundamentally different kind of intelligence from conversational AI. It’s conversational AI with a voice interface wrapped around it. The reasoning, the context tracking, the dialogue management—those are the same capabilities. What voice AI adds is the ability to operate through spoken language in real time, with all the additional complexity that introduces: handling interruptions, managing turn-taking, producing natural-sounding speech, and doing all of it with sub-500ms latency. Ultimately, conversational AI is how the system thinks. Voice AI is how it talks. How they relate Voice AI depends on conversational AI to be useful. Without the intelligence layer (intent recognition, context tracking, and coherent response generation), a voice system is just a phone menu with better audio. The voice interface makes the interaction accessible through speech. The conversational AI makes the interaction worth having. The relationship goes one way, though. Every voice AI system uses conversational AI underneath it. But conversational AI doesn’t require voice. A text-based chatbot, messaging bot, or AI assistant embedded in a ticketing system are conversational AI without any voice component. It’s not really a question of whether you need conversational AI or voice AI. It’s better to ask: does your use case require voice? If yes, you need voice AI—which means you also need conversational AI as the foundation. If the interaction is text-based, you need conversational AI without the voice layer. Voice AI vs. conversational AI: Key differences Side by side, the differences get a lot clearer. Here’s the breakdown across the criteria that matter most for teams building or buying AI for customer service. When to use conversational AI without voice Text-based conversational AI makes sense when your customers primarily engage through chat, messaging, or digital channels. And when the nature of the interaction doesn’t require the immediacy of a phone call. Support chat on a website WhatsApp automation AI-assisted email triage Messaging bots for transactional notifications These are all conversational AI use cases where voice doesn’t add much and may introduce unnecessary friction. Not every customer wants to speak out loud, especially in public, at work, or when the question is simple enough to type in thirty seconds. Text-based conversational AI is also typically faster to deploy, easier to test, and simpler to update. You can iterate on response quality, test new flows, and review transcripts without dealing with audio quality, latency optimisation, or the additional infrastructure that voice requires. If your primary support and engagement channels are digital and your customers are comfortable typing, starting with text-based conversational AI often makes more sense than jumping straight to voice. When you need voice AI specifically Voice AI makes sense when the use case is inherently telephonic, time-sensitive, or requires the kind of nuance that text alone doesn’t capture. Inbound phone support: Customers call because they want to talk to someone, or because they’ve always called, or because the issue feels urgent enough that they don’t want to wait for a chat response. An AI that can answer that call, understand the issue, and resolve it in the same interaction replaces one of the most expensive and frustrating moments in customer service. Outbound calling: Appointment reminders, fraud alerts, lead follow-up, proactive outreach for at-risk customers. These interactions are harder to execute over text because they require real-time dialogue. Context: Tone, urgency, frustration, hesitation—these are signals that a voice AI system can detect and respond to. A customer who speaks with audible frustration is communicating something beyond the literal words, and a well-designed voice AI system can adjust its approach accordingly. Finally, voice AI matters when your customers are less likely to engage through digital channels. These might be older demographics, industries where phone is still the primary contact method, or use cases where hands-free interaction is a practical requirement. Do you need both? For most businesses building serious customer engagement infrastructure: yes. The customers who prefer chat aren’t going away. Neither are the customers who pick up the phone. A complete AI engagement strategy handles both with a single connected experience rather than two separate systems that don’t know about each other. And that’s where Twilio Conversations can help. Conversation Orchestrator connects voice, SMS, WhatsApp, and chat into one continuous conversation record. Conversation Memory gives every agent (AI or human) persistent customer context across channels. Conversation Relay handles the voice AI layer: low-latency STT and TTS, bring-your-own-LLM, HIPAA-eligible. Agent Connect lets you plug your own AI agents into Twilio channels without rebuilding your communications infrastructure. Your customers are going to use both voice and text. The question is whether your stack connects them. Start for free or contact sales to talk through your use case. Frequently asked questions What’s the difference between voice AI and conversational AI? Conversational AI is the intelligence layer that understands human language and generates contextually relevant responses, regardless of channel. Voice AI is conversational AI delivered through spoken language. It adds speech-to-text and text-to-speech components so the interaction happens via voice. Is voice AI a type of conversational AI? Yes. Voice AI is a specific application of conversational AI that operates through spoken language. The reasoning, intent recognition, and dialogue management capabilities come from conversational AI. Voice AI adds the speech interface on top to convert spoken input to text, process it through the conversational AI layer, and convert the response back to speech. Can conversational AI work without voice? Yes. Text-based chatbots, messaging bots, AI assistants in ticketing systems, and email AI are all forms of conversational AI that don’t use voice. Does Twilio support both voice AI and conversational AI? Yes. Twilio Conversation Relay handles voice AI, combining low-latency STT and TTS with bring-your-own-LLM flexibility. The broader Twilio Conversations platform connects voice, SMS, WhatsApp, and chat into a single conversation layer, so the conversational AI intelligence and customer context are shared across every channel. To learn more about Twilio conversations, visit here .
Score: 29🌐 MovesJul 13, 2026https://www.cio.com/article/4194911/voice-ai-vs-conversational-ai-whats-the-difference.html - Journal Profile: Edward Balassanian uses AI to build startups in weeks, not years
Edward Balassanian entered the University of Washington at just 16, through its early entrance program, and graduated at 19. He spent the next five years as a software engineer at Microsoft. He's now a serial entrepreneur.
- People think Mitch McConnell’s hospital photo is AI—and AI isn’t helping
From bunnies jumping on a trampoline at night to Norwegian soccer player Erling Haaland getting scared by his own reflection, the more that AI -generated content makes its way into our social feeds, the harder it becomes to differentiate what’s false from what’s real. And while the rise of skepticism is unsurprising, it’s proving to be an even bigger problem when the stakes are high. Following the death of Republican Sen. Lindsey Graham of South Carolina on Saturday, users flocked to social media to share memes and speculation about the health of another Republican—Mitch McConnell. The senator from Kentucky, who was admitted to a hospital due to a fall, had not been seen since Graham’s death announcement, fueling rumors that he had also passed away. His team proceeded to try and prove the senator’s well-being the traditional way: issuing a statement and releasing a recent photo of McConnell in seemingly good health. But for an online public that’s grown accustomed to being tricked by AI, photographic evidence was deemed insufficient. Instead, it’s sparked its own rabbit hole of responses. What’s a picture even worth? Some of the initial reactions poked fun at the situation. Take late-night talk show host Jimmy Kimmel, who posted a parody photo substituting McConnell’s face for his own. The caption on Kimmel’s official Instagram read : “For those who’ve been asking, I’m feeling great.” But for others, the tone of the reaction was more conspiratorial, with many users online believing the photo to be fake or AI-generated. [Photo: Mitch McConnell /Facebook] “Mitch McConnell may or may not be alive. But his staff are definitely dying a slow death watching the AI photo they released yesterday get ripped to shreds,” a user said on X , despite no credible evidence of the image being AI. Many users paid special attention to the newspaper next to McConnell, with fake images circulating that featured warped text and gibberish, as is common with AI-generated images. However, the original image posted by McConnell’s team does not actually look like that. Additionally, the newspaper has since been identified as the Sunday sports section of The Washington Post . Turning to AI for a ruling Perhaps ironically, other skeptics turned to AI itself to try and verify the image. “ @grok , analyze this image for Ai, also focus on the image in the newspaper and find it, if real, when it was published and from what newspaper?” one user said on X, tagging the in-app AI chatbot. Grok responded: “The photo is AI-generated (SynthID watermark detected by OpenAI tool; confirmed fake by Snopes, Cincinnati Enquirer, Courier Journal). McConnell’s office released no such image—pure hoax.” The AI bot continued : “The newspaper (and photo inside) is also AI-fabricated. No real paper or date matches; entire scene is synthetic,” despite the newspaper spread actually existing. When challenged on the conclusion by the original user, who provided the newspaper spread to Grok, the AI stood behind its original—albeit false—judgment. Others turned to Google Lens for clarity, uploading McConnell’s photo to the search engine, with the AI summary returning a hallucinated response, indicating the image was taken in 2023. Skepticism around McConnell’s health state and the response to it are not entirely surprising. Public trust in the government is among the lowest it’s been in seven decades, with only around 17% believing that Washington will “ do what is right ,” according to Pew Research. To an already distrustful public, the way McConnell’s team has navigated the senator’s hospital stay—in secrecy—lends itself as a catalyst for theories, a similar treatment that then-President Joe Biden received when he was seeking reelection amid growing age and health concerns in 2024. But as public trust continues to erode, the widespread use of convincing AI images adds a new layer of complexity. While unfounded conspiracy theories have long been commonplace online, (remember Pizzagate?), the recent and rapid discourse arising from McConnell’s photo is symptomatic of a more recent trend—in which users are fatigued and skeptical of AI content, yet reliant on it at the same time. “Funny memes about Mitch McConnell aside, the replies are a mess,” one user noted on X. “The fact that people have to ask Grok if this photo is AI, and then they base their entire worldview on what the AI says, is not a good sign of what’s to come.”
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