Speaker 1: Welcome to AI assembled the top AI news for small business.
Speaker 1: I'm Chris daily and each week I bring you the
Speaker 1: most important AI developments that can transform your business. Let's
Speaker 1: dive into this week's top stories. There is a quiet
Speaker 1: counter movement building against the handful of tech giants that
Speaker 1: dominate AI to day. It is called Current Ai. It
Speaker 1: is a non profit and its ambition is to build open,
Speaker 1: public AI infrastructure the way the early World Wide Web
Speaker 1: was built as a shared resource rather than a private
Speaker 1: toll road. Current ai is backed by roughly four hundred
Speaker 1: million dollars in initial funding. That money comes from the
Speaker 1: French government, the Ford Foundation, the MacArthur Foundation, Google deep Mind,
Speaker 1: and sales Force, among others. Last week, the organization launched
Speaker 1: an open source AI chackbot called Alpha Chat, and last
Speaker 1: month it deployed three point two million dollars in grants
Speaker 1: to public interest AI projects in Kenya, Lebanon, and the
Speaker 1: Brazilian Amazon. Those grants are funding local language models, cultural
Speaker 1: preservation tools and AI built by and four communities that
Speaker 1: the big frontier labs are frankly ignoring. Here is what happened,
Speaker 1: and here is why it matters, and here is what
Speaker 1: to do.
Speaker 2: About it. What happened is that a serious, well funded
Speaker 2: alternative to the closed, subscription based AI world is finally
Speaker 2: getting off the ground. Why it matters is that if
Speaker 2: the only AI your business can access is owned by
Speaker 2: three or four American companies, you are one pricing change
Speaker 2: or one policy change away from being cut off. Now
Speaker 2: the important part, which is what a small or mid
Speaker 2: sized business should actually do. Number one, put Alpha Chat
Speaker 2: and the other open models current AI is funding on
Speaker 2: your evaluation list this quarter. You do not have to switch.
Speaker 2: You just need a working plan B for the day
Speaker 2: open AI or Anthropic raises prices on you, and that
Speaker 2: day is coming. Number two. If your business operates in
Speaker 2: a non English market or serves a community whose language
Speaker 2: is under represented, check the current AI grant list. Some
Speaker 2: of the models being funded right now will speak your
Speaker 2: customer's language better than g P T or claud ever
Speaker 2: will Number three, if you have any interest in your
Speaker 2: data staying on infrastructure, you can audit open source Public
Speaker 2: interest AI is the only long term answer. Start experimenting
Speaker 2: now at low stakes so you are not scrambling later.
Speaker 2: Knowing this story exists is only the first step. The
Speaker 2: move is to actually pilot one of these tools before
Speaker 2: your competitors do. Now to a story that could quietly
Speaker 2: reshape health care, insurance, and eventually what your employee benefits
Speaker 2: look like. Researchers at the University of Hong Kong have
Speaker 2: built an AI tool called cardiomic Score. It is an
Speaker 2: AI powered blood test from a single blood draw. It
Speaker 2: reads two thousand, nine hundred and twenty proteins and one
Speaker 2: hundred and sixty eight metabolites in your blood stream, and
Speaker 2: it uses a deep learning model to predict your risk
Speaker 2: of six major cardiovascular diseases, including heart attack, stroke, and
Speaker 2: heart failure up to fifteen years before any symptoms show up.
Speaker 2: Let that sink in fifteen years of advance warning. The
Speaker 2: model was trained and validated on a very large data
Speaker 2: set from the UK Biobank, and it beat traditional risk
Speaker 2: scores meaningfully in head to head comparisons. It is published
Speaker 2: in a peer reviewed journal, not a press release. This
Speaker 2: is real. Here is what happened, why it matters, and
Speaker 2: what to do about it. What happened is that AI
Speaker 2: just took cardiovascular medicine from reactive to genuinely predictive. Why
Speaker 2: it matters for a small business owner is that The
Speaker 2: cost of a preventable heart attack, whether it is you,
Speaker 2: a co founder, a key employee, or a family member,
Speaker 2: is measured in millions of dollars and sometimes in the
Speaker 2: survival of the business. Once tests like cardiomic score reach
Speaker 2: clinical rollout, they change the math on preventive care, on
Speaker 2: group health premiums, and eventually on wellness program design. Now
Speaker 2: the important part, which is the do this now list
Speaker 2: Number one. If you offer group health benefits, put multiomic
Speaker 2: biomarker screening on your radar for next year's plan review.
Speaker 2: Ask your broker directly whether early adopter carriers will start
Speaker 2: covering advanced risk stratification tests. The first carriers to do
Speaker 2: so will price aggressively to win business. Number Two, for
Speaker 2: yourself and any key person in your company whose absence
Speaker 2: would hurt the business, Look into concierge or executive physical
Speaker 2: programs that already offer proteomic and metabolomic panels. They are
Speaker 2: not cheap, but they exist, and the delta versus a
Speaker 2: standard physical is enormous. Number Three. Update your key person insurance.
Speaker 2: If a fifteen year advance warning becomes clinically standard, underwriting
Speaker 2: will shift and the businesses that document proactive screening for
Speaker 2: their leadership will get better terms. The headline here is
Speaker 2: a science store. The move for you is an insurance
Speaker 2: and benefits move. Do not let this one sit in
Speaker 2: the interesting but not urgent pile.
Speaker 3: Now to Shanghai and a model launch that quietly changes
Speaker 3: the competitive picture for anyone paying for frontier AI. At
Speaker 3: the World Artificial Intelligence Conference in Shanghai this past week,
Speaker 3: Ali Baba previewed its next flagship large language model. It
Speaker 3: is called Quen three point eight Max Preview and it
Speaker 3: is a two point four trillion parameter model for context
Speaker 3: that is roughly ten times the size of the largest
Speaker 3: model Ali Baba shipped just a year ago, and it
Speaker 3: puts Quen in the same weight class as the biggest
Speaker 3: closed models coming out of American labs. Ali Baba's Quen
Speaker 3: team is publicly positioning the new model as trailing only
Speaker 3: Anthropics top tier system, which they referred to as Claude
Speaker 3: Fable five, and beating or matching essentially everyone else on
Speaker 3: standard benchmarks. Now, benchmarks come with the usual caveats. Vendors
Speaker 3: pick the tests that flatter them. Preview models are not
Speaker 3: the same as generally available models, but the direction is unmistakable.
Speaker 3: A high quality Chinese frontier model from a company that
Speaker 3: has been aggressively pricing its AI services to gain market share,
Speaker 3: is now genuinely in the top tier. So here is
Speaker 3: what happened, why it matters, and what to do about it.
Speaker 3: What happened is that the frontier AI market went from
Speaker 3: a two or three horse race all American to a
Speaker 3: four or five horse race with serious Chinese competition. Why
Speaker 3: it matters is pricing. Every time a credible new frontier
Speaker 3: model launches, per token prices on comparable models fall. Ali
Speaker 3: Baba has historically undercut US competitors by fifty to eighty
Speaker 3: percent on API pricing, and there is no reason to
Speaker 3: think this generation will be different. Now the important part
Speaker 3: Number one, ask your current AI vendor in writing for
Speaker 3: their price roadmap through the next twelve months. Then quietly
Speaker 3: run a technical evaluation of quen on the exact workloads
Speaker 3: you use AI for today, coding, summarization, customer support, data extraction,
Speaker 3: whatever it is. Do not do this because you want
Speaker 3: to switch. Do it because leverage in your next renewal
Speaker 3: conversation requires a real alternative sitting on your desk. Number two.
Speaker 3: If your workload does not require top of the line reasoning,
Speaker 3: and honestly, most SMB workloads do not. Price sensitive, open
Speaker 3: weight or lower cost models are already good enough. The
Speaker 3: gap between frontier and good enough is shrinking every quarter.
Speaker 3: Every dollar you spend on frontier capability you did not
Speaker 3: need is a dollar you did not spend on hiring,
Speaker 3: marketing or product. Number three, be careful about data residency
Speaker 3: and compliance if you operate in the US, the EU,
Speaker 3: or in regulated industries. Using a Chinese model for anything
Speaker 3: involving customer data is not a simple decision. Get your
Speaker 3: privacy council involved before you pipe real data through any
Speaker 3: non domestic model. Use these tools for internal experimentation and
Speaker 3: non sensitive tasks. First. The takeaway is not that you
Speaker 3: should abandon Anthropic or open AI. The takeaway is that
Speaker 3: you now have real leverage in the negotiation, and you
Speaker 3: should use it. This week's other big under the radar story,
Speaker 3: Anthropic pushed enterprise customers from flat rate to full usage
Speaker 3: based billing back in April, and GitHub Copilot followed weeks later. Meanwhile,
Speaker 3: a KPMG survey of over two thousand executives found nearly
Speaker 3: one in three has no idea where their AI costs
Speaker 3: are actually coming from, and Uber publicly admitted it burned
Speaker 3: through its entire twenty twenty six AI coding budget in
Speaker 3: four months. The pattern is clear. The AI bill is
Speaker 3: coming due, and the businesses that will thrive are the
Speaker 3: ones that treat AI spending like a P and L
Speaker 3: line item, not a magic wand which brings us to
Speaker 3: the point of this whole show.
Speaker 2: Here is something worth saying out loud. Every AI newsletter,
Speaker 2: every AI podcast, every AI briefing you subscribe to will
Speaker 2: tell you what happened This week. Current Ai launched a
Speaker 2: blood test predicts heart attacks fifteen years out, Ali Baba
Speaker 2: shipped to two point four trillion parameter model. Great. Now,
Speaker 2: what Knowing what is happening is only part of the news. Frankly,
Speaker 2: it is the easy part. The hard part, and the
Speaker 2: actually valuable part is figuring out what to do about
Speaker 2: it before your competitor does. That is what this show
Speaker 2: tries to do every week. So let's put a bow
Speaker 2: on it with the do this now list for the
Speaker 2: week of July twentieth from the Current Ai story this week,
Speaker 2: put one open source model on your evaluation list not
Speaker 2: to switch to have a plan B and if you
Speaker 2: operate in a non English speaking market, look at what
Speaker 2: current AI is funding in your region. You may find
Speaker 2: a model that fits your customers better than anything from
Speaker 2: San Francisco from the Cardiomomic score story this month. Ask
Speaker 2: your health benefits broker to questions when will advanced multi
Speaker 2: omic screening be a covered benefit and is there an
Speaker 2: early adopter carrier we should be talking to. Then, for
Speaker 2: key people in your business, look into a proteomic panel
Speaker 2: through a concierge health provider. Yes, it costs real money,
Speaker 2: so does replacing your co founder From the Ali Baba
Speaker 2: Quenn story. Before your next AI vendor renewal and no
Speaker 2: later than ninety days from now, run a real technical
Speaker 2: bake off of your workloads against at least one alternative model.
Speaker 2: Document the results, bring them to the renewal conversation. That
Speaker 2: single hour of preparation is worth more in dollar terms
Speaker 2: than almost anything else on your calendar this quarter, and
Speaker 2: the metapoint which applies to every AI story you will
Speaker 2: read this year. When you hear a headline, ask three questions,
Speaker 2: what actually happened, Why does it matter for a business
Speaker 2: my size? And what specifically am I going to do
Speaker 2: differently this week because of it. If you cannot answer
Speaker 2: that third question, you have not really absorbed the news,
Speaker 2: You have just consumed it. The businesses that will win
Speaker 2: the next two years are not the ones that read
Speaker 2: the most about AI. They're the ones that build the
Speaker 2: tightest loop between hearing news and acting on it. Make
Speaker 2: that loop tighter starting this week. That is the whole game.
Speaker 2: See you next time.
Speaker 1: That's it for this week's AI assembled the top AI
Speaker 1: news for small business. If you found this valuable, share
Speaker 1: it with a fellow business owner. And if you want
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Speaker 1: Slash ai ready until next week, Keep innovating and keep
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